Teses / dissertações: "Sound events"

1

Hay, Timothy Deane. "MAX-DOAS measurements of bromine explosion events in McMurdo Sound, Antarctica". Thesis, University of Canterbury. Physics and Astronomy, 2010. http://hdl.handle.net/10092/5394.

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Reactive halogen species (RHS) are responsible for ozone depletion and oxidation of gaseous elemental mercury and dimethyl sulphide in the polar boundary layer, but the sources and mechanisms controlling their catalytic reaction cycles are still not completely understood. To further investigate these processes, ground– based Multi–Axis Differential Optical Absorption Spectroscopy (MAX-DOAS) observations of boundary layer BrO and IO were made from a portable instrument platform in McMurdo Sound during the Antarctic spring of 2006 and 2007. Measurements of surface ozone, temperature, pressure, humidity, and wind speed and direction were also made, along with fourteen tethersonde soundings and the collection of snow samples for mercury analysis. A spherical multiple scattering Monte Carlo radiative transfer model (RTM) was developed for the simulation of box-air-mass-factors (box-AMFs), which are used to determine the weighting functions and forward model differential slant column densities (DSCDs) required for optimal estimation. The RTM employed the backward adjoint simulation technique for the fast calculation of box-AMFs for specific solar zenith angles (SZA) and MAX-DOAS measurement geometries. Rayleigh and Henyey-Greenstein scattering, ground topography and reflection, refraction, and molecular absorption by multiple species were included. Radiance and box-AMF simulations for MAX-DOAS measurements were compared with nine other RTMs and showed good agreement. A maximum a posteriori (MAP) optimal estimation algorithm was developed to retrieve trace gas concentration profiles from the DSCDs derived from the DOAS analysis of the measured absorption spectra. The retrieval algorithm was validated by performing an inversion of artificial DSCDs, simulated from known NO2 profiles. Profiles with a maximum concentration near the ground were generally well reproduced, but the retrieval of elevated layers was less accurate. Retrieved partial vertical column densities (VCDs) were similar to the known values, and investigation of the averaging kernels indicated that these were the most reliable retrieval product. NO₂ profiles were also retrieved from measurements made at an NO₂ measurement and profiling intercomparison campaign in Cabauw, Netherlands in July 2009. Boundary layer BrO was observed on several days throughout both measurement periods in McMurdo Sound, with a maximum retrieved surface mixing ratio of 14.4±0.3 ppt. The median partial VCDs up to 3km were 9.7±0.07 x 10¹² molec cm ⁻ in 2007, with a maximum of 2.3±0.07 x 10¹³ molec cm⁻², and 7.4±0.06 x 10¹² molec cm⁻² in 2006, with a maximum of 1.05 ± 0.07 x 1013 molec cm⁻². The median mixing ratio of 7.5±0.5 ppt for 2007 was significantly higher than the median of 5.2±0.5 ppt observed in 2006, which may be related to the more extensive first year sea ice in 2007. These values are consistent with, though lower than estimated boundary layer BrO concentrations at other polar coastal sites. Four out of five observed partial ozone depletion events (ODEs) occurred during strong winds and blowing snow, while BrO was present in the boundary layer in both stormy and calm conditions, consistent with the activation of RHS in these two weather extremes. Air mass back trajectories, modelled using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, indicated that the events were locally produced rather than transported from other sea ice zones. Boundary layer IO mixing ratios of 0.5–2.5±0.2 ppt were observed on several days. These values are low compared to measurements at Halley and Neumayer Stations, as well as mid-latitudes. Significantly higher total mercury concentrations observed in 2007 may be related to the higher boundary layer BrO concentrations, but further measurements are required to verify this.

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2

Giannoulis, Dimitrios. "Recognition of sound sources and acoustic events in music and environmental audio". Thesis, Queen Mary, University of London, 2014. http://qmro.qmul.ac.uk/xmlui/handle/123456789/9130.

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Hearing, together with other senses, enables us to perceive the surrounding world through sensory data we constantly receive. The information carried in this data allow us to classify the environment and the objects in it. In modern society the loud and noisy acoustic environment that surrounds us makes the task of "listening" quite challenging, probably more so than ever before. There is a lot of information that has to be filtered to separate the sounds we want to hear at from unwanted noise and interference. And yet, humans, as other living organisms, have a remarkable ability to identify and track the sounds they want, irrespectively of the number of them, the degree of overlap and the interference that surrounds them. To this day, the task of building systems that try to "listen" to the surrounding environment and identify sounds in it the same way humans do is a challenging one, and even though we have made steps towards reaching human performance we are still a long way from building systems able to identify and track most if not all the different sounds within an acoustic scene. In this thesis, we deal with the tasks of recognising sound sources or acoustic events in two distinct cases of audio – music and more generic environmental sounds. We reformulate the problem and redefine the task associated with each case. Music can also be regarded as a multisound source environment where the different sound sources (musical instruments) activate at different times, and the task of recognising the musical instruments is then a central part of the more generic process of automatic music transcription. The principal question we address is whether we could develop a system able to recognise musical instruments in a multi-instrument scenario where many different instruments are active at the same time, and for that we draw influence from human performance. The proposed system is based on missing feature theory and we find that the method is able to retain high performance even under the most adverse of listening conditions (i.e. low signal-to-noise ratio). Finally, we propose a technique to fuse this system with another that deals with automatic music transcription in an attempt to inform and improve the overall performance. For a more generic environmental audio scene, things are less clear and the amount of research conducted in the area is still scarce. The central issue here, is to formulate the problem of sound recognition, define the subtasks and associated difficulties. We have set up and run a worldwide challenge and created datasets that is intended to enable researchers to perform better quality research in the field. We have also developed proposed systems that could serve as baseline techniques for future research and also compared existing state-of-the-art algorithms to one another, and also against human performance, in an effort to highlight strengths and weaknesses of existing methodologies.

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PAPETTI, Stefano. "Sound modeling issues in interactive sonification - From basic contact events to synthesis and manipulation tools". Doctoral thesis, Università degli Studi di Verona, 2010. http://hdl.handle.net/11562/340961.

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Questa tesi affronta una varietà di temi di ricerca, spaziando dalla interazione uomo-macchina alla modellizzazione fisica. Ciò che unisce queste ampie aree di interesse è l'idea di utilizzare simulazioni numeriche di fenomeni acustici basate sulla fisica, al fine di implementare interfacce uomo-macchina che offrano feedback sonoro coerente con l'interazione dell'utente. A questo proposito, negli ultimi anni sono nate numerose nuove discipline che vanno sotto il nome di -- per citarne alcune -- auditory display, sonificazione e sonic interaction design. In questa tesi vengono trattate la progettazione e la realizzazione di algoritmi audio efficienti per la sonificazione interattiva. A tale scopo si fa uso di tecniche di modellazione fisica di suoni ecologici (everyday sounds), ovvero suoni che non rientrano nelle famiglie del parlato e dei suoni musicali.
The work presented in this thesis ranges over a variety of research topics, spacing from human-computer interaction to physical-modeling. What combines such broad areas of interest is the idea of using physically-based computer simulations of acoustic phenomena in order to provide human-computer interfaces with sound feedback which is consistent with the user interaction. In this regard, recent years have seen the emergence of several new disciplines that go under the name of -- to cite a few -- auditory display, sonification and sonic interaction design. This thesis deals with the design and implementation of efficient sound algorithms for interactive sonification. To this end, the physical modeling of everyday sounds is taken into account, that is sounds not belonging to the families of speech and musical sounds.

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4

Olvera, Zambrano Mauricio Michel. "Robust sound event detection". Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0324.

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De l'industrie aux applications d'intérêt général, l'analyse automatique des scènes et événements sonores permet d'interpréter le flux continu de sons quotidiens. Une des principales dégradations rencontrées lors du passage des conditions de laboratoire au monde réel est due au fait que les scènes sonores ne sont pas composées d'événements isolés mais de plusieurs événements simultanés. Des différences entre les conditions d'apprentissage et de test surviennent aussi souvent en raison de facteurs extrinsèques, tels que le choix du matériel d'enregistrement et des positions des microphones, et de facteurs intrinsèques aux événements sonores, tels que leur fréquence d'occurrence, leur durée et leur variabilité. Dans cette thèse, nous étudions des problèmes d'intérêt pratique pour les tâches d'analyse sonore afin d'atteindre la robustesse dans des scénarios réels.Premièrement, nous explorons la séparation des sons ambiants dans un scénario pratique dans lequel plusieurs événements sonores de courte durée avec des caractéristiques spectrales à variation rapide (c'est-à-dire des sons d'avant-plan) se produisent simultanément à des sons stationnaires d'arrière-plan. Nous introduisons la tâche de séparation du son d'avant-plan et d'arrière-plan et examinons si un réseau de neurones profond avec des informations auxiliaires sur les statistiques du son d'arrière-plan peut différencier les caractéristiques spectro-temporelles à variation rapide et lente. De plus, nous explorons l'usage de la normalisation de l'énergie par canal (PCEN) comme prétraitement et la capacité du modèle de séparation à généraliser à des classes sonores non vues à l'apprentissage. Les résultats sur les mélanges de sons isolés à partir des jeux de données DESED et Audioset démontrent la capacité de généralisation du système de séparation proposé, qui est principalement due à PCEN.Deuxièmement, nous étudions comment améliorer la robustesse des systèmes d'analyse sonore dans des conditions d'apprentissage et de test différentes. Nous explorons deux tâches distinctes~: la classification de scène sonore (ASC) avec des matériels d'enregistrement différents et l'apprentissage de systèmes de détection d'événements sonores (SED) avec des données synthétiques et réelles.Dans le contexte de l'ASC, sans présumer de la disponibilité d'enregistrements capturés simultanément par les matériels d'enregistrement d'apprentissage et de test, nous évaluons l'impact des stratégies de normalisation et d'appariement des moments et leur intégration avec l'adaptation de domaine antagoniste non supervisée. Nos résultats montrent les avantages et les limites de ces stratégies d'adaptation appliquées à différentes étapes du pipeline de classification. La meilleure stratégie atteint les performances du domaine source dans le domaine cible.Dans le cadre de la SED, nous proposons un prétraitement basé sur PCEN avec des paramètres appris. Ensuite, nous étudions l'apprentissage conjoint du système de SED et de branches de classification auxiliaires qui catégorisent les sons en avant-plan ou arrière-plan selon leurs propriétés spectrales. Nous évaluons également l'impact de l'alignement des distributions des données synthétiques et réelles au niveau de la trame ou du segment par transport optimal. Enfin, nous intégrons une stratégie d'apprentissage actif dans la procédure d'adaptation. Les résultats sur le jeu de données DESED indiquent que ces méthodes sont bénéfiques pour la tâche de SED et que leur combinaison améliore encore les performances sur les scènes sonores réelles
From industry to general interest applications, computational analysis of sound scenes and events allows us to interpret the continuous flow of everyday sounds. One of the main degradations encountered when moving from lab conditions to the real world is due to the fact that sound scenes are not composed of isolated events but of multiple simultaneous events. Differences between training and test conditions also often arise due to extrinsic factors such as the choice of recording hardware and microphone positions, as well as intrinsic factors of sound events, such as their frequency of occurrence, duration and variability. In this thesis, we investigate problems of practical interest for audio analysis tasks to achieve robustness in real scenarios.Firstly, we explore the separation of ambient sounds in a practical scenario in which multiple short duration sound events with fast varying spectral characteristics (i.e., foreground sounds) occur simultaneously with background stationary sounds. We introduce the foreground-background ambient sound separation task and investigate whether a deep neural network with auxiliary information about the statistics of the background sound can differentiate between rapidly- and slowly-varying spectro-temporal characteristics. Moreover, we explore the use of per-channel energy normalization (PCEN) as a suitable pre-processing and the ability of the separation model to generalize to unseen sound classes. Results on mixtures of isolated sounds from the DESED and Audioset datasets demonstrate the generalization capability of the proposed separation system, which is mainly due to PCEN.Secondly, we investigate how to improve the robustness of audio analysis systems under mismatched training and test conditions. We explore two distinct tasks: acoustic scene classification (ASC) with mismatched recording devices and training of sound event detection (SED) systems with synthetic and real data.In the context of ASC, without assuming the availability of recordings captured simultaneously by mismatched training and test recording devices, we assess the impact of moment normalization and matching strategies and their integration with unsupervised adversarial domain adaptation. Our results show the benefits and limitations of these adaptation strategies applied at different stages of the classification pipeline. The best strategy matches source domain performance in the target domain.In the context of SED, we propose a PCEN based acoustic front-end with learned parameters. Then, we study the joint training of SED with auxiliary classification branches that categorize sounds as foreground or background according to their spectral properties. We also assess the impact of aligning the distributions of synthetic and real data at the frame or segment level based on optimal transport. Finally, we integrate an active learning strategy in the adaptation procedure. Results on the DESED dataset indicate that these methods are beneficial for the SED task and that their combination further improves performance on real sound scenes

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5

Beeferman, Leah. "JOURNEYS INTO THE UNKNOWN: A SERIES OF SCIENCE ARCHITECTURE TASKS AND EVENTS, SPACE-BOUND EXPLORATIONS AND FAR-TRAVELS, DISCOVERIES AND MISSES (NEAR AND FAR), IMAGINATIVE SPACE-GAZING AND RELATED INVESTIGATIONS, OBSERVATIONS, ORBITS, AND OTHER REPETITIOUS MONITORING TASKS". VCU Scholars Compass, 2010. http://scholarscompass.vcu.edu/etd/2164.

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This thesis expansively and inclusively puts forth the imaginings, research, processes and experiences behind my two thesis exhibitions, "Journeys into the unknown: a series of science architecture tasks and events, space-bound explorations and far-travels, discoveries and misses (near and far), imaginative space-gazing and related investigations, observations, orbits, and other repetitious monitoring tasks" and "Timed travel: asystematic accounts of regular and geometrical timekeeping, orbital flight, repetitive rotations and other journeys into actual time and slow space." It begins with an abstract interpretation of the dial: a tool not limited to scientific measurement but, instead, a gauge of an object’s overall position and general status. Equal parts scientific information, abstracted and fictionalized instruments and facts, and the personal experiences which provided these concrete informational elements with psychological and metaphorical meaning, this document is as much a record of time as it is an elucidation of my artistic practice and methodology.

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VESPERINI, FABIO. "Deep Learning for Sound Event Detection and Classification". Doctoral thesis, Università Politecnica delle Marche, 2019. http://hdl.handle.net/11566/263536.

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I recenti progressi riguardanti l’elaborazione del segnale acustico e le tecniche di machine learning hanno permesso lo sviluppo di tecnologie innovative per l’ana- lisi automatica di eventi sonori. In particolare, uno degli approcci attualmente piu` in voga in questo ambito consiste nell’impiego di tecniche di Deep Learning (DL). Tradizionalmente, tali algoritmi si basavano su tecniche di di modellazio- ne statistica come i Gaussian Mixture Models, gli Hidden Markov Models o le Support Vector Machines, ma il recente ritorno di interesse verso gli strumenti di apprendimento automatico come il DL ha condotto a risultati incoraggianti. Questa tesi riporta uno stato dell’arte aggiornato e propone diversi metodi basati su deep neural networks (DNN) per il Sound Event Detection (SED) ed il Sound Event Classification (SEC), congintamente ad una panoramica sulle procedure e le metriche di valutazione utilizzate in questo campo di ricerca. In particolare, la tendenza recente mostra un ampio impiego di reti neurali di tipo convoluzionale (CNN) per il SED ed il SEC. Questo lavoro include anche approcci innovativi basati sull’architettura DNN siamese o sulle nuove unita` computazionali chiamate Capsule. La maggior parte dei sistemi sono stati pro- gettati in occasione di challenge internazionali. Cio` ha consentito l’accesso a dataset pubblici e la possibilita` di confrontare su una base comune le prestazioni dei sistemi proposti dai team di ricerca piu` competitivi. I casi di studio riportati fanno riferimento ad applicazioni rivolte ad una gran- de varieta` di scenari che includono tra gli altri la diagnosi non invasiva, il monitoraggio bio-acustico e la classificazione delle condizioni della superficie stradale. Tra le complessita` a cui si deve fare fronte per permettere l’applicazione questi sistemi in ambienti reali vi sono lo sbilanciamento dei dataset, diversi setup di acquisizione, eventuali disturbi acustici e la polifonia. In particolare, un algoritmo per il SED polifonico puo` essere considerato come un sistema in grado di eseguire contemporaneamente il rilevamento e la classificazione degli eventi che si verificano nel flusso audio.
The recent progress on acoustic signal processing and machine learning techniques have enabled the development of innovative technologies for automatic analysis of sound events. In particular, nowadays one of the hottest approach to this problem lays on the exploitation of Deep Learning techniques. As further proof, in several occasion neural architectures originally designed for other multimedia domains have been successfully proposed to process the audio signal. Indeed, although these technologies have been faced for a long time by statistical modelling algorithms such as Gaussian Mixture Models, Hidden Markov Models or Support Vector Machines, the new breakthrough of machine learning for audio processing has lead to encouraging results into the addressed tasks. Hence, this thesis reports an up-to-date state of the art and proposes several reliable DNN-based methods for Sound Event Detection (SED) and Sound Event Classification (SEC), with an overview of the Deep Neural Network (DNN) architectures used on purpose and of the evaluation procedures and metrics used in this research field. According to the recent trend, which shows an extensive employment of Convolutional Neural Networks (CNNs) for both SED and SEC tasks, this work reports also rather new approaches based on the Siamese DNN architecture or the novel Capsule computational units. Most of the reported systems have been designed in the occasion of international challenges. This allowed the access to public datasets, and to compare systems proposed by the most competitive research teams on a common basis. The case studies reported in this dissertation refer to applications in a variety of scenarios, ranging from unobtrusive health monitoring, audio-based surveillance, bio-acoustic monitoring and classification of the road surface conditions. These tasks face numerous challenges, particularly related to their application in real-life environments. Among these issues there are unbalancing of datasets, different acquisition setups, acoustic disturbance (i.e., background noise, reverberation and cross-talk) and polyphony. In particular, since multiple events are very likely to overlap in real life audio, two algorithms for polyphonic SED are reported in this thesis. A polyphonic SED algorithm can be considered as system which is able to perform contemporary detection - determining onset and offset time of the sound events - and classification - assigning a label to each of the events occurring in the audio stream.

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7

Jackson, Asti Joy. "Structure of Sound". Thesis, Virginia Tech, 2016. http://hdl.handle.net/10919/73778.

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This thesis creates a complementarity relationship with the use of timber and concrete as primary structural and accent materials. Key elements of this thesis include (1) The development of a wood latticing system (2) Stairs that posses a strong sculptural language (3) The Lantern, a free standing lobby/box office, clad in wood and glass (4) Circulation towers that accommodate balcony seating. Studies of these elements went through many iterations resulting in over one hundred drawings. Progression of these drawings are directed to the interpretation of building form and the interaction with the site. These concepts are then implemented in the design of a multifaceted music venue located on a hillside in the New River Valley. Minutes from the college town of Blacksburg, Virginia this event complex caters to an array of musical functions. Spaces include The Lantern, which is a multipurpose lobby/lounge, the main auditorium, and an outdoor amphitheater.
Master of Architecture

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Fonseca, Eduardo. "Training sound event classifiers using different types of supervision". Doctoral thesis, Universitat Pompeu Fabra, 2021. http://hdl.handle.net/10803/673067.

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The automatic recognition of sound events has gained attention in the past few years, motivated by emerging applications in fields such as healthcare, smart homes, or urban planning. When the work for this thesis started, research on sound event classification was mainly focused on supervised learning using small datasets, often carefully annotated with vocabularies limited to specific domains (e.g., urban or domestic). However, such small datasets do not support training classifiers able to recognize hundreds of sound events occurring in our everyday environment, such as kettle whistles, bird tweets, cars passing by, or different types of alarms. At the same time, large amounts of environmental sound data are hosted in websites such as Freesound or YouTube, which can be convenient for training large-vocabulary classifiers, particularly using data-hungry deep learning approaches. To advance the state-of-the-art in sound event classification, this thesis investigates several strands of dataset creation as well as supervised and unsupervised learning to train large-vocabulary sound event classifiers, using different types of supervision in novel and alternative ways. Specifically, we focus on supervised learning using clean and noisy labels, as well as self-supervised representation learning from unlabeled data. The first part of this thesis focuses on the creation of FSD50K, a large-vocabulary dataset with over 100h of audio manually labeled using 200 classes of sound events. We provide a detailed description of the creation process and a comprehensive characterization of the dataset. In addition, we explore architectural modifications to increase shift invariance in CNNs, improving robustness to time/frequency shifts in input spectrograms. In the second part, we focus on training sound event classifiers using noisy labels. First, we propose a dataset that supports the investigation of real label noise. Then, we explore network-agnostic approaches to mitigate the effect of label noise during training, including regularization techniques, noise-robust loss functions, and strategies to reject noisy labeled examples. Further, we develop a teacher-student framework to address the problem of missing labels in sound event datasets. In the third part, we propose algorithms to learn audio representations from unlabeled data. In particular, we develop self-supervised contrastive learning frameworks, where representations are learned by comparing pairs of examples computed via data augmentation and automatic sound separation methods. Finally, we report on the organization of two DCASE Challenge Tasks on automatic audio tagging with noisy labels. By providing data resources as well as state-of-the-art approaches and audio representations, this thesis contributes to the advancement of open sound event research, and to the transition from traditional supervised learning using clean labels to other learning strategies less dependent on costly annotation efforts.
El interés en el reconocimiento automático de eventos sonoros se ha incrementado en los últimos años, motivado por nuevas aplicaciones en campos como la asistencia médica, smart homes, o urbanismo. Al comienzo de esta tesis, la investigación en clasificación de eventos sonoros se centraba principalmente en aprendizaje supervisado usando datasets pequeños, a menudo anotados cuidadosamente con vocabularios limitados a dominios específicos (como el urbano o el doméstico). Sin embargo, tales datasets no permiten entrenar clasificadores capaces de reconocer los cientos de eventos sonoros que ocurren en nuestro entorno, como silbidos de kettle, sonidos de pájaros, coches pasando, o diferentes alarmas. Al mismo tiempo, websites como Freesound o YouTube albergan grandes cantidades de datos de sonido ambiental, que pueden ser útiles para entrenar clasificadores con un vocabulario más extenso, particularmente utilizando métodos de deep learning que requieren gran cantidad de datos. Para avanzar el estado del arte en la clasificación de eventos sonoros, esta tesis investiga varios aspectos de la creación de datasets, así como de aprendizaje supervisado y no supervisado para entrenar clasificadores de eventos sonoros con un vocabulario extenso, utilizando diferentes tipos de supervisión de manera novedosa y alternativa. En concreto, nos centramos en aprendizaje supervisado usando etiquetas sin ruido y con ruido, así como en aprendizaje de representaciones auto-supervisado a partir de datos no etiquetados. La primera parte de esta tesis se centra en la creación de FSD50K, un dataset con más de 100h de audio etiquetado manualmente usando 200 clases de eventos sonoros. Presentamos una descripción detallada del proceso de creación y una caracterización exhaustiva del dataset. Además, exploramos modificaciones arquitectónicas para aumentar la invariancia frente a desplazamientos en CNNs, mejorando la robustez frente a desplazamientos de tiempo/frecuencia en los espectrogramas de entrada. En la segunda parte, nos centramos en entrenar clasificadores de eventos sonoros usando etiquetas con ruido. Primero, proponemos un dataset que permite la investigación del ruido de etiquetas real. Después, exploramos métodos agnósticos a la arquitectura de red para mitigar el efecto del ruido en las etiquetas durante el entrenamiento, incluyendo técnicas de regularización, funciones de coste robustas al ruido, y estrategias para rechazar ejemplos etiquetados con ruido. Además, desarrollamos un método teacher-student para abordar el problema de las etiquetas ausentes en datasets de eventos sonoros. En la tercera parte, proponemos algoritmos para aprender representaciones de audio a partir de datos sin etiquetar. En particular, desarrollamos métodos de aprendizaje contrastivos auto-supervisados, donde las representaciones se aprenden comparando pares de ejemplos calculados a través de métodos de aumento de datos y separación automática de sonido. Finalmente, reportamos sobre la organización de dos DCASE Challenge Tasks para el tageado automático de audio a partir de etiquetas ruidosas. Mediante la propuesta de datasets, así como de métodos de vanguardia y representaciones de audio, esta tesis contribuye al avance de la investigación abierta sobre eventos sonoros y a la transición del aprendizaje supervisado tradicional utilizando etiquetas sin ruido a otras estrategias de aprendizaje menos dependientes de costosos esfuerzos de anotación.

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Pahar, Madhurananda. "A novel sound reconstruction technique based on a spike code (event) representation". Thesis, University of Stirling, 2016. http://hdl.handle.net/1893/23025.

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This thesis focuses on the re-generation of sound from a spike based coding system. Three different types of spike based coding system have been analyzed. Two of them are biologically inspired spike based coding systems i.e. the spikes are generated in a similar way to how our auditory nerves generate spikes. They have been called AN (Auditory Nerve) spikes and AN Onset (Amplitude Modulated Onset) spikes. Sounds have been re-generated from spikes generated by both of those spike coding technique. A related event based coding technique has been developed by Koickal and the sounds have been re-generated from spikes generated by Koickal's spike coding technique and the results are compared. Our brain does not reconstruct sound from the spikes received from auditory nerves, it interprets it. But by reconstructing sounds from these spike coding techniques, we will be able to identify which spike based technique is better and more efficient for coding different types of sounds. Many issues and challenges arise in reconstructing sound from spikes and they are discussed. The AN spike technique generates the most spikes of the techniques tested, followed by Koickal's technique (54.4% lower) and the AN Onset technique (85.6% lower). Both subjective and objective types of testing have been carried out to assess the quality of reconstructed sounds from these three spike coding techniques. Four types of sounds have been used in the subjective test: string, percussion, male voice and female voice. In the objective test, these four types and many other types of sounds have been included. From the results, it has been established that AN spikes generates the best quality of decoded sounds but it produces many more spikes than the others. AN Onset spikes generates better quality of decoded sounds than Koickal's technique for most of sounds except choir type of sounds and noises, however AN Onset spikes produces 68.5% fewer spikes than Koickal's spikes. This provides evidences that AN Onset spikes can outperform Koickal's spikes for most of the sound types.

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Labbé, Etienne. "Description automatique des événements sonores par des méthodes d'apprentissage profond". Electronic Thesis or Diss., Université de Toulouse (2023-....), 2024. http://www.theses.fr/2024TLSES054.

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Dans le domaine de l'audio, la majorité des systèmes d'apprentissage automatique se concentrent sur la reconnaissance d'un nombre restreint d'événements sonores. Cependant, lorsqu'une machine est en interaction avec des données réelles, elle doit pouvoir traiter des situations beaucoup plus variées et complexes. Pour traiter ce problème, les annotateurs ont recours au langage naturel, qui permet de résumer n'importe quelle information sonore. La Description Textuelle Automatique de l'Audio (DTAA ou Automated Audio Captioning en anglais) a été introduite récemment afin de développer des systèmes capables de produire automatiquement une description de tout type de son sous forme de texte. Cette tâche concerne toutes sortes d'événements sonores comme des sons environnementaux, urbains, domestiques, des bruitages, de la musique ou de parole. Ce type de système pourrait être utilisé par des personnes sourdes ou malentendantes, et pourrait améliorer l'indexation de grandes bases de données audio. Dans la première partie de cette thèse, nous présentons l'état de l'art de la tâche de DTAA au travers d'une description globale des jeux de données publics, méthodes d'apprentissage, architectures et métriques d'évaluation. À l'aide de ces connaissances, nous présentons ensuite l'architecture de notre premier système de DTAA, qui obtient des scores encourageants sur la principale métrique de DTAA nommée SPIDEr : 24,7 % sur le corpus Clotho et 40,1 % sur le corpus AudioCaps. Dans une seconde partie, nous explorons de nombreux aspects des systèmes de DTAA. Nous nous focalisons en premier lieu sur les méthodes d'évaluations au travers de l'étude de SPIDEr. Pour cela, nous proposons une variante nommée SPIDEr-max, qui considère plusieurs candidats pour chaque fichier audio, et qui montre que la métrique SPIDEr est très sensible aux mots prédits. Puis, nous améliorons notre système de référence en explorant différentes architectures et de nombreux hyper-paramètres pour dépasser l'état de l'art sur AudioCaps (SPIDEr de 49,5 %). Ensuite, nous explorons une méthode d'apprentissage multitâche visant à améliorer la sémantique des phrases générées par notre système. Enfin, nous construisons un système de DTAA généraliste et sans biais nommé CONETTE, pouvant générer différents types de descriptions qui se rapprochent de celles des jeux de données cibles. Dans la troisième et dernière partie, nous proposons d'étudier les capacités d'un système de DTAA pour rechercher automatiquement du contenu audio dans une base de données. Notre approche obtient des scores comparables aux systèmes dédiés à cette tâche, alors que nous utilisons moins de paramètres. Nous introduisons également des méthodes semi-supervisées afin d'améliorer notre système à l'aide de nouvelles données audio non annotées, et nous montrons comment la génération de pseudo-étiquettes peut impacter un modèle de DTAA. Enfin, nous avons étudié les systèmes de DTAA dans d'autres langues que l'anglais : français, espagnol et allemand. De plus, nous proposons un système capable de produire les quatre langues en même temps, et nous le comparons avec les systèmes spécialisés dans chaque langue
In the audio research field, the majority of machine learning systems focus on recognizing a limited number of sound events. However, when a machine interacts with real data, it must be able to handle much more varied and complex situations. To tackle this problem, annotators use natural language, which allows any sound information to be summarized. Automated Audio Captioning (AAC) was introduced recently to develop systems capable of automatically producing a description of any type of sound in text form. This task concerns all kinds of sound events such as environmental, urban, domestic sounds, sound effects, music or speech. This type of system could be used by people who are deaf or hard of hearing, and could improve the indexing of large audio databases. In the first part of this thesis, we present the state of the art of the AAC task through a global description of public datasets, learning methods, architectures and evaluation metrics. Using this knowledge, we then present the architecture of our first AAC system, which obtains encouraging scores on the main AAC metric named SPIDEr: 24.7% on the Clotho corpus and 40.1% on the AudioCaps corpus. Then, subsequently, we explore many aspects of AAC systems in the second part. We first focus on evaluation methods through the study of SPIDEr. For this, we propose a variant called SPIDEr-max, which considers several candidates for each audio file, and which shows that the SPIDEr metric is very sensitive to the predicted words. Then, we improve our reference system by exploring different architectures and numerous hyper-parameters to exceed the state of the art on AudioCaps (SPIDEr of 49.5%). Next, we explore a multi-task learning method aimed at improving the semantics of sentences generated by our system. Finally, we build a general and unbiased AAC system called CONETTE, which can generate different types of descriptions that approximate those of the target datasets. In the third and last part, we propose to study the capabilities of a AAC system to automatically search for audio content in a database. Our approach obtains competitive scores to systems dedicated to this task, while using fewer parameters. We also introduce semi-supervised methods to improve our system using new unlabeled audio data, and we show how pseudo-label generation can impact a AAC model. Finally, we studied the AAC systems in languages other than English: French, Spanish and German. In addition, we propose a system capable of producing all four languages at the same time, and we compare it with systems specialized in each language

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11

Kahl, Stefan. "Identifying Birds by Sound: Large-scale Acoustic Event Recognition for Avian Activity Monitoring". Universitätsverlag Chemnitz, 2019. https://monarch.qucosa.de/id/qucosa%3A36986.

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Automated observation of avian vocal activity and species diversity can be a transformative tool for ornithologists, conservation biologists, and bird watchers to assist in long-term monitoring of critical environmental niches. Deep artificial neural networks have surpassed traditional classifiers in the field of visual recognition and acoustic event classification. Still, deep neural networks require expert knowledge to design, train, and test powerful models. With this constraint and the requirements of future applications in mind, an extensive research platform for automated avian activity monitoring was developed: BirdNET. The resulting benchmark system yields state-of-the-art scores across various acoustic domains and was used to develop expert tools and public demonstrators that can help to advance the democratization of scientific progress and future conservation efforts.
Die automatisierte Überwachung der Vogelstimmenaktivität und der Artenvielfalt kann ein revolutionäres Werkzeug für Ornithologen, Naturschützer und Vogelbeobachter sein, um bei der langfristigen Überwachung kritischer Umweltnischen zu helfen. Tiefe künstliche neuronale Netzwerke haben die traditionellen Klassifikatoren im Bereich der visuellen Erkennung und akustische Ereignisklassifizierung übertroffen. Dennoch erfordern tiefe neuronale Netze Expertenwissen, um leistungsstarke Modelle zu entwickeln, trainieren und testen. Mit dieser Einschränkung und unter Berücksichtigung der Anforderungen zukünftiger Anwendungen wurde eine umfangreiche Forschungsplattform zur automatisierten Überwachung der Vogelaktivität entwickelt: BirdNET. Das daraus resultierende Benchmark-System liefert state-of-the-art Ergebnisse in verschiedenen akustischen Bereichen und wurde verwendet, um Expertenwerkzeuge und öffentliche Demonstratoren zu entwickeln, die dazu beitragen können, die Demokratisierung des wissenschaftlichen Fortschritts und zukünftige Naturschutzbemühungen voranzutreiben.

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Erik, Rosshagen. "Sync Event : The Ethnographic Allegory of Unsere Afrikareise". Thesis, Stockholms universitet, Institutionen för mediestudier, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-131291.

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The thesis aims at a critical reflexion on experimental ethnography with a special focus on the role of sound. A reassessment of its predominant discourse, as conceptualized by Cathrine Russell, is paired with a conceptual approach to film sound and audio-vision. By reactivating experimental filmmaker Peter Kubelka’s concept sync event and its aesthetic realisation in Unsere Afrikareise (Our Trip to Africa, Peter Kubelka, 1966) the thesis provide a themed reflection on the materiality of film as audiovisual relation. Sync event is a concept focused on the separation and meeting of image and sound to create new meanings, or metaphors. By reintroducing the concept and discussing its implication in relation to Michel Chion’s audio-vision, the thesis theorizes the audiovisual relation in ethnographic/documentary film more broadly. Through examples from the Russian avant-garde and Surrealism the sync event is connected to a historical genealogy of audiovisual experiments. With James Clifford’s notion ethnographic allegory Unsere Afrikareise becomes a case in point of experimental ethnography at work. The sync event is comprehended as an ethnographic allegory with the audience at its focal point; a colonial critique performed in the active process of audio-viewing film.

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Widmann, Andreas, Thomas Gruber, Teija Kujala, Mari Tervaniemi e Erich Schröger. "Binding Symbols and Sounds: Evidence from Event-Related Oscillatory Gamma- Band Activity". Oxford University Press, 2007. https://ul.qucosa.de/id/qucosa%3A32714.

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The present study intended to examine the neural basis of audiovisual integration, hypothetically achieved by synchronized gamma-band oscillations (30--80 Hz) that have been suggested to integrate stimulus features and top--down information. To that end, we studied the impact of visual symbolic information on early auditory sensory processing of upcoming sounds. In particular, we used a symbol-to-sound--matching paradigm in which simple score-like patterns predict corresponding sound patterns. Occasionally, a single sound is incongruent with the corresponding element of the visual pattern. In response to expected sounds congruent with the corresponding visual symbol, a power increase of phase-locked (evoked) activity in the 40-Hz band was observed peaking 42-ms poststimulus onset. Thus, for the first time, we demonstrated that the comparison process between a neural model, the expectation, and the current sensory input is implemented at very early levels of auditory processing. Subsequently, expected congruent sounds elicited a broadband power increase of non--phase-locked (induced)activity peaking 152-ms poststimulus onset, which might reflect the formation of a unitary event representation including both visual and auditory aspects of the stimulation. Gamma-band responses were not present for unexpected incongruent sounds. A model explaining the anticipatory activation of cortical auditory representations and the match of experience against expectation is presented

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14

Rosshagen, Erik. "Sync Event : The Ethnographic Allegory of Unsere Afrikareise". Thesis, Stockholms universitet, Filmvetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-183273.

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The thesis aims at a critical reflexion on experimental ethnography with a special focus on the role of sound. A reassessment of its predominant discourse, as conceptualized by Cathrine Russell, is paired with a conceptual approach to film sound and audiovision. By reactivating experimental filmmaker Peter Kubelka’s concept sync event and its aesthetic realisation in Unsere Afrikareise (Our Trip to Africa, Peter Kubelka, 1966) the thesis provide a themed reflection on the materiality of film as audiovisual relation. Sync event is a concept focused on the separation and meeting of image and sound to create new meanings, or metaphors. By reintroducing the concept and discussing its implication in relation to Michel Chion’s audio-vision, the thesis theorizes the audiovisual relation in ethnographic/documentary film more broadly.Through examples from the Russian avant-garde and Surrealism the sync event is connected to a historical genealogy of audiovisual experiments. With James Clifford’s notion ethnographic allegory Unsere Afrikareise becomes as a case in point of experimental ethnography at work. The sync event is comprehended as an ethnographic allegory with the audience at its focal point; a colonial critique performed in the active process of audio-viewing film.

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15

Brooks, Julian. "Being sound : FLOSS, flow and event in the composition and ensemble performance of free open computer music". Thesis, University of Huddersfield, 2016. http://eprints.hud.ac.uk/id/eprint/31370/.

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This commentary describes my recent approach to writing compositions for the ensemble performance of computer music. Drawing on experimental music and improvisation, I contend that such music is best considered in terms of people’s situated and relational interplay. The compositional and performative question that permeates this thesis is ‘what can we do, in this time and space, with these tools available to us?’. As themes of equality and egalitarian access underpin this work throughout, I highlight my engagement with Free Libre Open Source Software (FLOSS) ideology and community, reflecting on how this achieves my aims. I describe my writing of text score compositions, making use of the term bounded improvisation, whose purposeful requirements for indeterminate realisation extends most current computer-based performance practice. Though no single strand of this research is perhaps unusual by itself, such an assemblage as that outlined above (incorporating composition, computer coding and ensemble performance practice) is, when allied to an understanding of electronic and computer music praxis, currently an underdeveloped approach. Such an approach I have thus chosen to term free open computer music. I incorporate two further pre-existing conceptual formulations to present a framework for constructing, reflecting on, and developing my work in this field. Firstly flow or 'immersed experience' is useful to explicate difficult to capture aspects of instrumental engagement and ensemble performance. Secondly, this portfolio of scores aims to produce well-constructed situations, facilitating spaces of flow which contain within their environments the opportunity for an event to take place. I present the outcomes of my practice as place-forming tactics that catalyse something to do, but not what to do, in performative spaces such as those described above. Such intentions define my aims for composition. These theoretical concerns, together with an allied consideration of the underpinning themes highlighted above, is a useful framework for refection and evaluation of this work.

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Maiste, Anita. "Human auditory event-related potentials to frequency changes in speech and non-speech sounds". Thesis, University of Ottawa (Canada), 1989. http://hdl.handle.net/10393/5899.

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This thesis presents two approaches investigating how the human auditory system processes the brief frequency changes that occur in speech sounds. Section 1 of the thesis consists of a critical review of the literature on human auditory event-related potentials (ERPs) and speech perception. Section 2 consists of three experiments evaluating ERPs to non-speech frequency changes. The experiments evaluated steady state and transient auditory evoked potentials (EPs) to tones that were sinusoidally modulated in frequency and to tones that alternated between two frequencies with a linear ramp. The tones were presented at modulation rates typical of average syllable production. The steady state responses to sinusoidal FM were small and difficult to record at both the first and second harmonics. Ramp FM evoked larger and more consistent second harmonic steady state responses than the sinusoidal FM. Only the ramp FM stimuli elicited transient EPs and these only at low modulation rates. These responses were larger to upward ramps than to downward ramps. The response to two simultaneously presented ramp FM tones differed from the sum of responses to the individual tones indicating some interaction in the processing of the two stimuli. Since the first study found that steady state responses were not as reliable as ERPs to discrete frequency changes, the second study used speech sounds containing discrete frequency changes. In Section 3 of the thesis computer-modified speech sounds from the /ba/ to /da/ continuum were presented to reading subjects as a train of standard speech sounds interspersed with two types of infrequent deviant speech sounds. One deviant stimulus lay within the same category as the standard and the other lay across the categorical boundary from the standard, but both were acoustically equidistant from the standard in terms of the second formant transition. When the standard stimulus was drawn from the /ba/ end of the continuum, the across-category deviants elicited a clear mismatch negativity (MMN) in the auditory event-related potential whereas the within-category deviants did not. This MMN began at about 60-120 ms after stimulus onset and was present for several hundred ms. These results suggest that categorical processing of speech sounds occurs independently of attention at an early echoic memory stage. When the standard stimulus was drawn from the /da/ end of the continuum, the MMN to across-category deviants was not larger than the MMN to within-category deviants. Grand mean waveforms suggested that both deviant stimuli elicited small MMNs. Although this may indicate processing along an acoustic continuum, the results of the psychophysical tests suggest that the standard stimulus in this condition was too close to the category boundary for the deviants to evoke a consistent categorical mismatch.

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Pieszek, Marika, Erich Schröger e Andreas Widmann. "Separate and concurrent symbolic predictions of sound features are processed differently". Universitätsbibliothek Leipzig, 2014. http://nbn-resolving.de/urn:nbn:de:bsz:15-qucosa-155242.

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The studies investigated the impact of predictive visual information about the pitch and location of a forthcoming sound on the sound processing. In Symbol-to-Sound matching paradigms, symbols induced predictions of particular sounds. The brain’s error signals (IR and N2b components of the event-related potential) were measured in response to occasional violations of the prediction, i.e. when a sound was incongruent to the corresponding symbol. IR and N2b index the detection of prediction violations at different levels, IR at a sensory and N2b at a cognitive level. Participants evaluated the congruency between prediction and actual sound by button press. When the prediction referred to only the pitch or only the location feature (Exp. 1), the violation of each feature elicited IR and N2b. The IRs to pitch and location violations revealed differences in the in time course and topography, suggesting that they were generated in feature-specific sensory areas. When the prediction referred to both features concurrently (Exp. 2), that is, the symbol predicted the sound´s pitch and location, either one or both predictions were violated. Unexpectedly, no significant effects in the IR range were obtained. However, N2b was elicited in response to all violations. N2b in response to concurrent violations of pitch and location had a shorter latency. We conclude that associative predictions can be established by arbitrary rule-based symbols and for different sound features, and that concurrent violations are processed in parallel. In complex situations as in Exp. 2, capacity limitations appear to affect processing in a hierarchical manner. While predictions were presumably not reliably established at sensory levels (absence of IR), they were established at more cognitive levels, where sounds are represented categorially (presence of N2b).

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Barton, Antony James. "Signal processing techniques for data reduction and event recognition in cough counting". Thesis, University of Manchester, 2013. https://www.research.manchester.ac.uk/portal/en/theses/signal-processing-techniques-for-data-reduction-and-event-recognition-in-cough-counting(dc73495a-35b0-4d17-a6f8-cc2f88008659).html.

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This thesis presents novel techniques for the reduction of audio recordings and signal processing techniques as part of cough recognition. Evidence collected shows the reduction technique to be effective and the recognition techniques to give consistent performance across different patients. Cough is one of the commonest symptoms reported by patients to GPs. Despite this, it remains a significantly unmet medical need. At present, there exists no practical and validated technique for assessing the efficacy of therapies to treat cough on a large enough scale. Research that is presently undertaken requires fitting a patient with a recording system which will record their coughing and all other sound for a predefined period, usually 24 hours or less. This audio is then counted manually by trained cough counters to produce counts for each record which can be used as data for cough studies. Research in this field is relatively new, but a number of attempts have been made to automate this process. None so far have shown sufficient reliability or precision to be of sufficient use. The aim of this research is to analyse from the ground up signal processing techniques which can aid cough research. Specifically, the research will look into data minimisation techniques to improve the efficiency of manual counting techniques and recognition algorithmsThe research has produced a published record reduction system which can reduce 24 hour cough records down to around 10% of their original size without compromising the statistics of subsequent manual counts. Additionally, a review of signal processing techniques for cough recognition has produced a robust event detection technique and measurement techniques which have shown remarkable consistency between patients and conditions. Throughout the research a clear understanding of the limitations and possible solutions are pursued and reported on to aid further progress on what is a young and developing research field.

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Trowitzsch, Ivo [Verfasser], Klaus [Akademischer Betreuer] Obermayer, Klaus [Gutachter] Obermayer, Dorothea [Gutachter] Kolossa e Thomas [Gutachter] Sikora. "Robust sound event detection in binaural computational auditory scene analysis / Ivo Trowitzsch ; Gutachter: Klaus Obermayer, Dorothea Kolossa, Thomas Sikora ; Betreuer: Klaus Obermayer". Berlin : Technische Universität Berlin, 2020. http://d-nb.info/1210055120/34.

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20

Natzén, Christopher. "The Coming of Sound Film in Sweden 1928-1932 : New and Old Technologies". Doctoral thesis, Stockholms universitet, Filmvetenskapliga institutionen, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-42168.

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This dissertation examines the coming of sound film in Sweden during the years 1928–1932, and the reception of mechanically recorded sounds both in the trade press and among audiences. The novelty of sound film opened up for a negotiation of the perception of sound and image, as it made visible the film medium’s technological construction, before this visibility was once more absorbed by the cinematic discourse. The conversion to sound film is considered from three perspectives -- technology, reception and practice -- as well as through the concept of intermediality, focussing how the audio-visual expression changed during this period. Chapter 1 “Image, Sound, Audience I: ‘Constructed’ sounds - the visibility of technology” deals with these issues prior to the conversion to sound, and the following intermediate years, until sound film had reached a certain equilibrium. Chapter 2 “Production – The Companies” deals with the production and the major Swedish sound companies. Particular attention is given to how formative music in their films transforms itself into a consistent use of non-diegetic music two years before this happened in Hollywood. Chapter 3 “Reception – The Cinemas” addresses the topic of the reception of the first sound films in Sweden during 1929. The argument is that the audience’s re-awakened awareness of the technology described in Chapter 1 was an active part in this process, and that their reactions led back into the advertising campaigns, making them participants in the cinematic event. Chapter 4 “Practice – The Musicians” continues this debate from a musician’s point of view. This chapter turns the focus upside down and looks at the arrival of sound film from a grass-roots perspective. While chapter 4 diverts somewhat in dwelling on issues that do not strictly deal with the conversion to sound, it serves to contextualise a technological invention that changed not only film production and reception, but also had very concrete social repercussions for those that created the sounds of music. Chapter 5 “Image, Sound, Audience II: ‘Authentic’ sounds - the disappearance of technology” dovetails with Chapter 1, addressing similar phenomena at a time when these had become fully integrated and the technology once more became invisible.

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Kahl, Stefan [Verfasser], Maximilian [Akademischer Betreuer] Eibl, Maximilian [Gutachter] Eibl, Marc [Gutachter] Ritter e Holger [Akademischer Betreuer] Klinck. "Identifying Birds by Sound: Large-scale Acoustic Event Recognition for Avian Activity Monitoring / Stefan Kahl ; Gutachter: Maximilian Eibl, Marc Ritter ; Maximilian Eibl, Holger Klinck". Chemnitz : Universitätsverlag Chemnitz, 2020. http://d-nb.info/1219664502/34.

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Mafe, Majena. "Soundage : a practice-led approach to Gertrude Stein, sound, and generative language". Thesis, Queensland University of Technology, 2013. https://eprints.qut.edu.au/63361/1/Majena_Mafe_Thesis.pdf.

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In this practice-led research project I work to show how a re-reading and a particular form of listening to the sound-riddled nature of Gertrude Stein's work, Two: Gertrude Stein and her Brother, presents us with a contemporary theory of sound in language. This theory, though in its infancy, is a particular enjambment of sounded language that presents itself as an event, engaged with meaning, with its own inherent voice. It displays a propensity through engagement with the 'other' to erupt into love. In this thesis these qualities are reverberated further through the work of Seth Kim-Cohen's notion of the non-cochlear, Simon Jarvis's notion of musical thinking, Jean-Jacques Lecercle's notion of délire or nonsense, Luce Irigaray's notion of jouissant love and the Bracha Ettinger's notion of the generative matrixial border space. This reading then is simultaneously paired with my own work of scoring and creating a digital opera from Stein's work, thereby testing and performing Stein's theory. In this I show how a re-reading and relistening to Stein's work can be significant to feminist ethical language frames, contemporary philosophy, sonic art theory and digital language frames. Further significance of this study is that when the reverberation of Stein's engagements with language through sound can be listened to, a pattern emerges, one that encouragingly problematizes subjectivity and interweaves genres/methods and means, creating a new frame for sound in language, one with its own voice that I call soundage.

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23

Klobása, Jiří. "Systém pro záznam a opakování událostí pro zvukové systémy". Master's thesis, Vysoké učení technické v Brně. Fakulta informačních technologií, 2015. http://www.nusl.cz/ntk/nusl-234948.

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This thesis deals with the design and implementation of system for recording and repeating of events for audio systems. The introductory part is devoted to the study of sound systems, their user interfaces and communication protocols that are used by audio systems. Hereafter the description of essential features of Mac OS X, as well as the characteristic of its user interface and principles of development on this platform, are given. The core of the thesis consists of the design of system for recording and repeating of events and the concept of events which specifies the reprezentation of events in the system and their subsequent processing. In~the end of the thesis is presented the implementation of the designed system for Mac OS X with respect to possible extensions of the system and its features.

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Rijo, Sara Marina Albino. "Técnicas de deep learning para detecção de eventos em áudio: treino de modelos acústicos a partir de sinais puros". Master's thesis, Universidade de Évora, 2018. http://hdl.handle.net/10174/22275.

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O vídeo é atualmente um dos recursos mais utilizados e em constante expansão no mundo digital, sendo que em 2019 será responsável por 80% do tráfego mundial de Internet. Neste panorama, surgiu a problemática da incapacidade humana e (até agora) tecnológica para descrever, interpretar e interagir com este elevado volume de dados multimédia. Assim, têm sido desenvolvidos esforços para encontrar formas de automatizar e melhorar o processo de análise de conteúdo de vídeo e consequentemente melhorar a eiciência, usabilidade e acessibilidade dos vídeos armazenados por milhões de pessoas em todo o mundo. Este processo pode focar-se na análise do som e imagem em simultâneo ou independentemente. Esta dissertação descreve a concretização de um projecto de análise de som, que consistiu no desenvolvimento e implementação de um sistema de classiicação de áudio utilizando uma abordagem baseada na utilização da waveform do som e redes neuronais, excluindo a convencional fase de extração de características habitualmente utilizada em aprendizagem máquina. Esta metodologia permite ultrapassar as limitações ao nível da ineicência temporal de abordagens típicamente utilizadas. Sendo o áudio um componente de relevo no vídeo, torna-se assim possível detectar e distinguir elementos de destaque, como por exemplo as partes mais cómicas, faladas ou musicais. Elaborou-se também um conjunto de dados de sons exclusivamente para o projecto, tendo em vista colmatar a utilização de dados de ‘laboratório’, isto é, obtidos em ambientes controlados, que induzem a falsos positivos e não representam a estocacidade do som no ‘mundo real’. Os resultados obtidos foram bastante satisfatórios, tanto pela rapidez do processo como pela sua precisão, que atingiu taxas de reconhecimento dos sons na ordem dos 90%; O vídeo é atualmente um dos recursos mais utilizados e em constante expansão no mundo digital, sendo que em 2019 será responsável por 80% do tráfego mundial de Internet. Neste panorama, surgiu a problemática da incapacidade humana e (até agora) tecnológica para descrever, interpretar e interagir com este elevado volume de dados multimédia. Assim, têm sido desenvolvidos esforços para encontrar formas de automatizar e melhorar o processo de análise de conteúdo de vídeo e consequentemente melhorar a eiciência, usabilidade e acessibilidade dos vídeos armazenados por milhões de pessoas em todo o mundo. Este processo pode focar-se na análise do som e imagem em simultâneo ou independentemente. Esta dissertação descreve a concretização de um projecto de análise de som, que consistiu no desenvolvimento e implementação de um sistema de classiicação de áudio utilizando uma abordagem baseada na utilização da waveform do som e redes neuronais, excluindo a convencional fase de extração de características habitualmente utilizada em aprendizagem máquina. Esta metodologia permite ultrapassar as limitações ao nível da ineicência temporal de abordagens típicamente utilizadas. Sendo o áudio um componente de relevo no vídeo, torna-se assim possível detectar e distinguir elementos de destaque, como por exemplo as partes mais cómicas, faladas ou musicais. Elaborou-se também um conjunto de dados de sons exclusivamente para o projecto, tendo em vista colmatar a utilização de dados de ‘laboratório’, isto é, obtidos em ambientes controlados, que induzem a falsos positivos e não representam a estocacidade do som no ‘mundo real’. Os resultados obtidos foram bastante satisfatórios, tanto pela rapidez do processo como pela sua precisão, que atingiu taxas de reconhecimento dos sons na ordem dos 90%; Abstract Deep Learning for Sound Event Detection Training acoustic models on waveforms Video is currently one of the most used media resources, it’s use is expanding worldwide and predictions point that by 2019 video will be responsible for 80% of the world’s internet traic. With this in mind the problem of the impossibility for humans and technology (so far) to describe, interpret and interact with this amount of multimedia data rouse. Thus eforts have been made to ind ways to automate and improve the video content analysis process and consequently better the eiciency, usability and accessibility of video stored by millions of people arround the world. This process can focus on the simultaneous analysis of image and sound or independently. This dissertation describes a project that consisted in the development and implementation of an audio classiication system using an emerging approach based on the use of the sound waveform and neural networks, excluding the convetional feature extraction phase normally used in machine learning. As the audio is an important component of video, this system allows detection of important elements like the funnyest parts, where is speech and where is music. The results were very satisfactory, both in terms of processing speed and precision, that reached classiication scores arround 90%.

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Ferroudj, Meriem. "Detection of rain in acoustic recordings of the environment using machine learning techniques". Thesis, Queensland University of Technology, 2015. https://eprints.qut.edu.au/82848/1/Meriem_Ferroudj_Thesis.pdf.

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This thesis is concerned with the detection and prediction of rain in environmental recordings using different machine learning algorithms. The results obtained in this research will help ecologists to efficiently analyse environmental data and monitor biodiversity.

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Afyonoglu, Kirbas Yeliz. "Neuronal activity to environmental sounds when presented together with semantically related words : An MMN study on monolingual and bilingual processing of homophones". Thesis, Stockholms universitet, Avdelningen för allmän språkvetenskap, 2019. http://urn.kb.se/resolve?urn=urn:nbn:se:su:diva-170303.

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Neuronal activity of monolingual and bilinguals to environmental sounds and words that are semantically related to them were studied using the mismatch negativity (MMN) component of event-related potentials. MMN was expected to reflect the language selection process in bilinguals on the bases of semantics and phonology. In this regard, as lexical stimuli, interlingual homophones ‘car’ and ‘kar’ (snow) were presented together with semantically related environmental sounds in a passive auditory oddball paradigm. The lexical stimuli were recorded by a native English speaker. Three Turkish-English late bilinguals and one native English speaker participated in the study. An early MMN was elicited in both groups with a distribution over the fronto-central and central areas across the scalp with highest peak amplitude at -2.5 with a 113 ms latency. This response indicates that participants of the study were sensitive to the acoustic changes in two different types of stimuli. The further investigation of the interplay between environmental sounds and semantics displayed no conclusive result due to lack of data. Finally, the brain responses gathered from the bilinguals were not enough to draw a conclusion. Whether the bilinguals were sensitive to the sub-phonemic cues in the presented auditory lexical stimuli or not were inconclusive.
Neuronal aktivitet av en- och tvåspråkiga till miljöljud och ord som är semantiskt relaterade till dem studerades med hjälp av Mismatch Negativity (MMN) komponent av event-relaterade potentialer. MMN förväntades spegla språkvalsprocessen i tvåspråkiga baserad på semantik och fonologi. I detta avseende presenterades interlingual-homofoner ’car’ (bil) och ’kar’ (snö) som lexikala stimuli tillsammans med semantiskt besläktade miljöljud i ett passivt auditivt oddball paradigm. De lexikala stimuli spelades in av en modersmålstalare av engelska. Tre turkiska-engelska sena tvåspråkiga och en modersmålstalare av engelska deltog i studien. En tidig MMN framkallades i båda grupperna med en fördelning över de främre central- och centrala områdena över skalp med amplitud vid -2,5 med 113 ms latens. Detta indikerar att deltagarna var sensitiva till de akustiska förändringarna mellan de två olika typerna av stimuli. Den vidare undersökningen av samspelet mellan miljöljud och semantik visade inget avgörande resultat. Dessutom, var det också ett inkonklusivt resultat som handlade om att huruvida tvåspråkiga deltagarna använde subfonemiska signalerna i de presenterade auditiva lexikala stimuli eller inte.

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Baczkowski, Antoine. "L'expérience festive au sein de la vie : pour une sociologie de la place des raves, des free parties et des teknivals dans le parcours biographique". Thesis, Besançon, 2014. http://www.theses.fr/2014BESA1025.

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Les raves, les free parties et les teknivals, sont des fêtes techno à l'origine d'une panique morale en France. L'histoire sociale de ces phénomènes est celle d'une répression d'État. Nous avons tâché de saisir (l'essence de) l'expérience de ces fêtes, compte tenu d'un marqueur temporel et biographique : l'événement marquant (Michèle Leclerc-Olive, 1997). Il s'est agi dans un premier temps, pour des teuffeurs volontaires, et membres de Sound Systems, de se raconter dans le cadre d'entretiens biographiques. Puis, dans un deuxième temps, d'identifier, .avec notre aide, ce qui a orienté, et décidé de leur parcours. Leur vie ne fut-elle que délire ? Jouissance esthétique ? Un « activiste » techno n'est-il marqué que par la fête ? Les récits de vie de Marc, de Fabrice, de Marie-Sophie et de Gino, nous ont permis de répondre à ces questions
Raves, free parties and teknivals are techno parties that, in France, are the origin of moral panic. Their social history and phenomena are those of state suppression. This thesis attempts to catch (the essence of) the experience of these parties given a temporal and biographical event: The notewor1hy event (Michèle Leclerc-Olive, 1997). ln the first place the ravers and other voluntary members from Sound Systems told about themselves within the frame of biographical interviews. Then, as a second step, the goal was to identify, with our help, what guided and decided their path. Was their life only a "blast"? An aesthetically pleasing? Would a techno "activist" be marked only by celebration? Life stories of Marc, Fabrice, Marie Sophie and Gino helped us to bring a clear answer to these questions

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Pollatou, Efpraxia. "Sounds of satire, echoes of madness : performance and evaluation in Cefalonia, Greece". Thesis, University of St Andrews, 2009. http://hdl.handle.net/10023/1016.

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This thesis is about the construction of 'satire' as an exclusive practice among the Cefalonian and hence proposes the term satiricity (satirikotita). It explores the construction of the category of the Cefalonian "madman" by means of dialogics between performance and evaluation. It is observed that the relation depends on three principles that obtain among audience members and a performer: conditioning the performance, participation in and observation of the performance and evaluation of it. Being one of the few anthropological studies on the Ionian islands of Greece, this thesis aims to contribute to the anthropology of the Ionian islands and of Cefalonia in particular. It looks at the relation between a town and a village on the ground of teasing events and refutes the argument of satire as an urban phenomenon only. It sets the elementary principles towards anthropology of satire and emphasizes the importance of studying everyday teasing events. It also contributes to understanding a 'native' researcher's presence in different ways. Satiricity is seen as a 'par excellence' feature that Cefalonians have. No matter if Cefalonia is a part of the Greek nation-state and people follow 'modern Greek culture', they still employ satiricity as a way of distancing themselves from Greeks. 'Distance' is forged on the basis of absolute exclusion of Greeks from having, practising and understanding satiricity in the way that Cefalonians do. The Conclusions leave the ground open for more investigation on teasing events and application of such viewpoints around other areas of the island, and of the Ionian islands or other Greek islands. I also point to studies looking at island and mainland teasing events and potential differences. After all, we need to examine not only how people construct the claim on the exclusivity of 'satire'. We need to examine how such a claim is applied, supported or contrasted and possibly rejected when Cefalonians engage with other Greeks away from the island.

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Guerrasio, Francesca. "Les territoires sonores de Salvatore Sciarrino. L’écoute écologique, le théâtre musical, l’esthétique figurale". Thesis, Paris 4, 2012. http://www.theses.fr/2012PA040046.

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Notre travail de recherche a pour objectif d’éclairer le parcours logique dissimulé derrière les compositions pour le théâtre de Salvatore Sciarrino, afin de réduire la distance entre l’artiste e le destinataire de ses œuvres. Nous avons réfléchi dans un premier temps aux conditions culturelles qui ont joué un rôle important et décisif dans la création du compositeur pour ensuite nous pencher sur l’observation, l’analyse et la compréhension de son premier essai d’esthétique : Le figure della musica da Beethoven a oggi. L’analyse des formes musicales individuées et formalisées par Sciarrino s’est révélée conséquente pour :a. mettre en évidence la forma mentis du compositeur et les innombrables aspects de sa personnalité ;b. déceler l’ensemble de normes et de lois qui sont à la base de son langage organique.Sans nous engager dans le domaine sémantique de la musique, nous avons néanmoins réfléchi avec Sciarrino sur le langage musical et sur la question de sa communication. La recherche du compositeur se présente en fait comme un cas particulier de création d’un langage conçu pour le domaine artistique en général et non pas exclusivement pour le domaine musical.Afin de retracer les aspects les plus singuliers de son travail artistique, nous avons mis l’accent sur l’un des concepts fondamentaux de son enseignement : la musique découle entièrement de la réalité sonore qui nous entoure et qui en constitue l’essence. L’événement sonore, conçu en tant qu’organisme vivant, renvoie à l’idée de Sciarrino d’une écoute écologique, qui traduit la faculté de transformation des sons naturels dans le langage musical, à travers une écoute en perspective.Le découpage dramatique et dramaturgique mis en œuvre par le compositeur propose à l’auditeur et à l’interprète de sa musique un véritable travail de perception, à la fois du texte et de la musique, et les plonge dans un monde caractérisé par l’incertitude et l’imperceptibilité. D’où l’originalité de sa recherche musicale et de ses projets dramaturgiques, qui n’ont pas pour objectif de faire coïncider la réalité visuelle avec la réalité sonore, mais de l’évoquer à travers des sons imperceptibles, à la limite du silence
The goal of this research is to shed light on the logical trail that is hidden behind Sciarrino’s compositions for theater; it will help us reduce the distance between the artist and the recipient of his works. At first, we will ponder the cultural circumstances, which played an important and decisive part in the composer’s artistic creations. Then, we will devote time to observe, analyze and understand his first writing on aesthetics : Les figure della musica da Beethoven a oggi.The analysis of the unique musical forms created by Sciarrino will prove useful as we :a. reveal the forma mentis of the composer and the innumerable aspects of his personality ;b. trace his organic language back to the system of norms and laws from which it originates.Without involving ourselves in the category of musical semantics, we will nonetheless consider musical language and its levels of communication. In fact, Sciarrino’s research appears as the special instance of a language that is being created for the artistic world in general and not exclusively for the musical world.In order to recount the most singular aspects of his artistic work, we will focus on one of the fundamental concepts of his teachings : that music derives entirely from the sonic reality, which surrounds us and which therefore constitutes its essence.The sonic event, conceived as a living organism, refers to the idea of ecological listening. It is the faculty of transforming natural sounds within a musical language, by listening in perspective.The dramatic and dramaturgic division put in place by Sciarrino offers the listener and the performer of his music a study on perception, of both text and music, and immerges them in a world characterized by uncertainty and imperceptibility. Hence the originality of his musical research and dramaturgic project, which goal is not to make the visual reality coincide with the sonic reality, but to evoke the former with imperceptible sounds, ones that border on silence

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Kempf, Alexandre. "Nonlinear encoding of sounds in the auditory cortex Temporal asymmetries in auditory coding and perception reflect multi-layered nonlinearities Cortical recruitment determines learning dynamics and strategy Interactions between nonlinear features in the mouse auditory cortex Context-dependent signaling of coincident auditory and visual events in primary visual cortex". Thesis, Sorbonne Paris Cité, 2018. http://www.theses.fr/2018USPCB085.

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Les objets perceptuels sont les unités élémentaires utilisées par le cerveau pour construire une représentation interne du monde a partir de signaux physiques, comme la lumière ou les ondes sonores. Alors que ces signaux sont d'abord traduit, par les récepteurs dans les organes périphériques, en signaux neuronaux, l'émergence d'objets perceptuels nécessite un traitement intensif dans le système nerveux central qui n'est pas encore entièrement connu. Il est intéressant de noter que les progrès récents de deep learning montrent qu'une séries d'opérations non linéaires et linéaires est très efficace pour catégoriser les objets perceptuels visuels et auditifs de la même manière que les humains. En revanche, la plupart des connaissances actuelles sur le système auditif se concentrent sur les transformations linéaires. Afin de comprendre la contribution des non-linéarités du système auditif à la perception, nous avons étudié l'encodage des sons avec une intensité croissante et une intensité décroissante dans le cortex auditif de la souris. Ces deux sons sont perçus avec une importance inégale malgré le fait qu'ils ont la même énergie physique et le même contenu spectral, un phénomène incompatible avec le traitement linéaire. En enregistrant l'activité de grandes populations corticales pour les sons montants et descendants, nous avons constaté que le cortex les encode avec des populations distinctes qui détectent des caractéristiques non linéaires, ce qui explique l'asymétrie perceptuelle. Nous avons également montré que, dans les modèles de reinforcement learning, la quantité d'activité neuronale déclenchée par un son impacte la vitesse et la stratégie d'apprentissage. Des effets très similaires ont été observés dans plusieurs taches de discrimination ou les sons provoquaient des réponses neuronales de différentes intensités. Ceci établit que les non-linéarités du système auditif ont un impact sur la perception et le comportement. Pour mieux identifier les non-linéarités qui influencent le codage des sons, nous avons ensuite enregistré l'activité d'environ 60 000 neurones échantillonnant toute la superficie du cortex auditif. Au-delà de l'organisation tonotopique à fine échelle découverte avec cet ensemble de données, nous avons identifié et quantifié 7 non-linéarités. Il est aussi intéressant de constater que différentes non-linéarités peuvent interagir entre elles d'une manière non triviale. La connaissance de ces interactions est importante pour affiner le modèle de traitement auditif. Enfin, nous nous sommes demandé si les processus non linéaires sont également importants pour l'intégration multisensorielle. Nous avons mesuré, par imagerie calcique, comment les images et les sons se combinent dans le cortex visuel et auditif. Nous n'avons trouvé aucune modulation du cortex auditif (L2/3) en réponse à des stimuli visuels. Nous avons observé que les entrées du cortex auditif dans le cortex visuel affectent les réponses visuelles concomitantes à un son. Nous avons constaté que les projections du cortex auditif au cortex visuel encode de préférence une caractéristique non linéaire particulière : l'apparition soudaine de sons fort. Par conséquent, l'activité du cortex visuel pour une image et un son fort est plus élevée que pour l'image seule ou combinée à un son faible. Ce résultat suggère que les sons forts sont pertinents du point de vue de comportement multisensoriel, peut-être pour indiquer la présence de nouveaux objets dans le champ visuel, ce qui pourrait représenter des menaces potentielles. En conclusion, nos résultats montrent que les non-linéarités sont omniprésentes dans le traitement du son par le cerveau et jouent également un rôle dans l'intégration de l'information auditive avec l'information visuelle. Il est non seulement crucial de tenir compte de ces non-linéarités pour comprendre comment se forment les représentations perceptuelles, mais aussi pour prédire l'impact de ces représentations sur le comportement
Perceptual objects are the elementary units used by the brain to construct an inner world representation of the environment from multiple physical sources, like light or sound waves. While the physical signals are first encoded by receptors in peripheral organs into neuroelectric signals, the emergence of perceptual object require extensive processing in the central nervous system which is not yet fully characterized. Interestingly, recent advances in deep learning shows that implementing series of nonlinear and linear operations is a very efficient way to create models that categorize visual and auditory perceptual objects similarly to humans. In contrast, most of the current knowledge about the auditory system concentrates on linear transformations. In order to establish a clear example of the contribution of auditory system nonlinearities to perception, we studied the encoding of sounds with an increasing intensity (up ramps) and a decreasing intensity (down ramps) in the mouse auditory cortex. Two behavioral tasks showed evidence that these two sounds are perceived with unequal salience despite carrying the same physical energy and spectral content, a phenomenon incompatible with linear processing. Recording the activity of large cortical populations for up- and down-ramping sounds, we found that cortex encodes them into distinct sets of non-linear features, and that asymmetric feature selection explained the perceptual asymmetry. To complement these results, we also showed that, in reinforcement learning models, the amount of neural activity triggered by a stimulus (e.g. a sound) impacts learning speed and strategy. Interestingly very similar effects were observed in sound discrimination behavior and could be explain by the amount of cortical activity triggered by the discriminated sounds. This altogether establishes that auditory system nonlinearities have an impact on perception and behavior. To more extensively identify the nonlinearities that influence sounds encoding, we then recorded the activity of around 60,000 neurons sampling the entire horizontal extent of auditory cortex. Beyond the fine scale tonotopic organization uncovered with this dataset, we identified and quantified 7 nonlinearities. We found interestingly that different nonlinearities can interact with each other in a non-trivial manner. The knowledge of these interactions carry good promises to refine auditory processing model. Finally, we wondered if the nonlinear processes are also important for multisensory integration. We measured how visual inputs and sounds combine in the visual and auditory cortex using calcium imaging in mice. We found no modulation of supragranular auditory cortex in response to visual stimuli, as observed in previous others studies. We observed that auditory cortex inputs to visual cortex affect visual responses concomitant to a sound. Interestingly, we found that auditory cortex projections to visual cortex preferentially channel activity from neurons encoding a particular non-linear feature: the loud onset of sudden sounds. As a result, visual cortex activity for an image combined with a loud sound is higher than for the image alone or combine with a quiet sound. Moreover, this boosting effect is highly nonlinear. This result suggests that loud sound onsets are behaviorally relevant in the visual system, possibly to indicate the presence of a new perceptual objects in the visual field, which could represent potential threats. As a conclusion, our results show that nonlinearities are ubiquitous in sound processing by the brain and also play a role in the integration of auditory information with visual information. In addition, it is not only crucial to account for these nonlinearities to understand how perceptual representations are formed but also to predict how these representations impact behavior

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House, Kayli. "Pilgrim carnival". Thesis, view full-text document. Access restricted to the University of North Texas campus, 2002. http://www.library.unt.edu/theses/open/20022/house%5Fkayli/index.htm.

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Thesis (M.M.)--University of North Texas, 2002.
A two-week event in four parts: invitation, installation, reception, and thank-you card. Installation for 2 hosts, 2 ushers, photographer, 4 posers, exerciser, sound persons, and blindfolded guests, with a mix of live and recorded sounds. Includes instructions for performance. Includes bibliographical references (p. 66-67).

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Lafay, Grégoire. "Simulation de scènes sonores environnementales : Application à l’analyse sensorielle et l’analyse automatique". Thesis, Ecole centrale de Nantes, 2016. http://www.theses.fr/2016ECDN0007/document.

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La présente thèse traite de l'analyse de scènes extraites d'environnements sonores, résultat auditif du mélange de sources émettrices distinctes et concomitantes. Ouvrant le champ des sources et des recherches possibles au-delà des domaines plus spécifiques que sont la parole ou la musique, l'environnement sonore est un objet complexe. Son analyse, le processus par lequel le sujet lui donne sens, porte à la fois sur les données perçues et sur le contexte de perception de ces données.Tant dans le domaine de la perception que de l'apprentissage machine, toute expérience suppose un contrôle fin de l'expérimentateur sur les stimuli proposés. Néanmoins, la nature de l'environnement sonore nécessite de se placer dans un cadre écologique, c'est à dire de recourir à des données réelles, enregistrées, plutôt qu'à des stimuli de synthèse. Conscient de cette problématique, nous proposons un modèle permettant de simuler, à partir d'enregistrements de sons isolés, des scènes sonores dont nous maîtrisons les propriétés structurelles -- intensité, densité et diversité des sources. Appuyé sur les connaissances disponibles sur le système auditif humain, le modèle envisage la scène sonore comme un objet composite, une somme de sons sources.Nous investissons à l'aide de cet outil deux champs d'application. Le premier concerne la perception, et la notion d'agrément perçu dans des environnements urbains. L'usage de données simulées nous permet d'apprécier finement l'impact de chaque source sonore sur celui-ci. Le deuxième concerne la détection automatique d'événements sonores et propose une méthodologie d'évaluation des algorithmes mettant à l'épreuve leurs capacités de généralisation
This thesis deals with environmental scene analysis, the auditory result of mixing separate but concurrent emitting sources. The sound environment is a complex object, which opens the field of possible research beyond the specific areas that are speech or music. For a person to make sense of its sonic environment, the involved process relies on both the perceived data and its context. For each experiment, one must be, as much as possible,in control of the evaluated stimuli, whether the field of investigation is perception or machine learning. Nevertheless, the sound environment needs to be studied in an ecological framework, using real recordings of sounds as stimuli rather than synthetic pure tones. We therefore propose a model of sound scenes allowing us to simulate complex sound environments from isolated sound recordings. The high level structural properties of the simulated scenes -- such as the type of sources, their sound levels or the event density -- are set by the experimenter. Based on knowledge of the human auditory system, the model abstracts the sound environment as a composite object, a sum of soundsources. The usefulness of the proposed model is assessed on two areas of investigation. The first is related to the soundscape perception issue, where the model is used to propose an innovative experimental protocol to study pleasantness perception of urban soundscape. The second tackles the major issue of evaluation in machine listening, for which we consider simulated data in order to powerfully assess the generalization capacities of automatic sound event detection systems

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"Re-Sonification of Objects, Events, and Environments". Doctoral diss., 2013. http://hdl.handle.net/2286/R.I.17897.

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abstract: Digital sound synthesis allows the creation of a great variety of sounds. Focusing on interesting or ecologically valid sounds for music, simulation, aesthetics, or other purposes limits the otherwise vast digital audio palette. Tools for creating such sounds vary from arbitrary methods of altering recordings to precise simulations of vibrating objects. In this work, methods of sound synthesis by re-sonification are considered. Re-sonification, herein, refers to the general process of analyzing, possibly transforming, and resynthesizing or reusing recorded sounds in meaningful ways, to convey information. Applied to soundscapes, re-sonification is presented as a means of conveying activity within an environment. Applied to the sounds of objects, this work examines modeling the perception of objects as well as their physical properties and the ability to simulate interactive events with such objects. To create soundscapes to re-sonify geographic environments, a method of automated soundscape design is presented. Using recorded sounds that are classified based on acoustic, social, semantic, and geographic information, this method produces stochastically generated soundscapes to re-sonify selected geographic areas. Drawing on prior knowledge, local sounds and those deemed similar comprise a locale's soundscape. In the context of re-sonifying events, this work examines processes for modeling and estimating the excitations of sounding objects. These include plucking, striking, rubbing, and any interaction that imparts energy into a system, affecting the resultant sound. A method of estimating a linear system's input, constrained to a signal-subspace, is presented and applied toward improving the estimation of percussive excitations for re-sonification. To work toward robust recording-based modeling and re-sonification of objects, new implementations of banded waveguide (BWG) models are proposed for object modeling and sound synthesis. Previous implementations of BWGs use arbitrary model parameters and may produce a range of simulations that do not match digital waveguide or modal models of the same design. Subject to linear excitations, some models proposed here behave identically to other equivalently designed physical models. Under nonlinear interactions, such as bowing, many of the proposed implementations exhibit improvements in the attack characteristics of synthesized sounds.
Dissertation/Thesis
Ph.D. Electrical Engineering 2013

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Freitas, João Pedro Alves de. "Uma Experiência de Produção Musical - Relatório de Estágio no Jazz ao Centro Clube – Salão Brazil". Master's thesis, 2020. http://hdl.handle.net/10316/93717.

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Relatório de Estágio do Mestrado em Estudos Artísticos apresentado à Faculdade de Letras
Uma Experiência de Produção MusicalEste relatório resume o trabalho que foi desenvolvido por mim entre 20 de outubro de 2019 e 1 de fevereiro de 2020 na Associação sem fins lucrativos Jazz ao Centro Clube (JACC). Este trabalho foi, maioritariamente realizado no Salão Brazil, espaço explorado pelo JACC.O Estágio teve como Orientadores José Miguel Pereira, Presidente do JACC e Adriana Ávila, Vice-Presidente do JACC. Este Relatório foi feito com a Orientação do Professor Doutor Paulo Estudante, do Departamento de História, Estudos Europeus, Arqueologia e Artes da Faculdade de Letras da Universidade de Coimbra.No começo deste trabalho, é feito um pequeno enquadramento teórico, principalmente, sobre políticas culturais e onde e de que forma estas atuam, com o objetivo de se chegar ao ponto de vista do associativismo e, por consequência, do trabalho desenvolvido no estágio e dos seus moldes. Para tal, começa-se por se procurar um conceito geral de Política Cultural. Com este estabelecido, segue-se o percurso destas políticas em Portugal e, por fim, no meio local, dos municípios. O passo seguinte resume a história do Jazz ao Centro Clube, desde a sua fundação. São também descritas as principais atividades da associação.De seguida, explicita-se detalhadamente, num Diário de Bordo compilado ao longo da duração do estágio, as tarefas levadas a cabo pelo estagiário nos diferentes dias e os contactos feitos com a restante equipa, como momentos de aprendizagem ou trabalho em conjunto. Avança-se, posteriormente, para uma descrição detalhada do trabalho de produção executado e das diversas tarefas, tentando explicar, com um formato a assemelhar-se a um tutorial, que passos são necessários para executar essas tarefas e para que é que estas são precisas.Faz-se o mesmo sobre o trabalho técnico, utilizando um caso real e simulando a montagem do material para um concerto da banda “PAUS”, como feito para o concerto desta do dia 24 de janeiro de 2020 no Salão Brazil.
An Experience in Musical ProductionThis report summarizes the work that was developed by me between October 20th, 2019 and February 1st, 2020 at the Nonprofit Association Jazz ao Centro Clube (JACC). This work was mostly carried out at Salão Brazil, the base of operations of JACC.The internship was oriented by José Miguel Pereira, President of JACC and Adriana Ávila, Vice President of JACC. This report was made under the guidance of Professor Paulo Estudante, from the Departamento de História, Estudos Europeus, Arqueologia e Artes da Faculdade de Letras da Universidade de Coimbra.At the beginning of this paper, a small theoretical framework is made, mainly about cultural policies and where and how they act, with the aim of reaching the point of view of associations and, consequently, of the work developed in the internship. To do this, we begin by looking for a general concept of Cultural Policies. With this established we follow the course of these policies in Portugal and, finally, in a local environment like counties. The next step was to detail the history of Jazz ao Centro Clube, from its. The main activities of the Association are also described.Then, the tasks carried out by the trainee on the different days and the contacts made with the rest of the team, such as moments of learning or working together, were detailed in a Journal that was compiled along the duration of the internship.After that, it proceeds to a detailed description of the production work performed and the various tasks, trying to explain, in a format similar to a tutorial, what steps are needed to perform these tasks and what they are needed for.The same is done about the technical work, using a real scenario and simulating the assembly of the material for a concert by the band “PAUS”, as done for their concert on January 24th, 2020 at Salão Brazil.

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Lin, Chang Hong, e 林昶宏. "A Study on Robust Sound Event Recognition". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/vg9tn5.

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博士
國立中央大學
資訊工程學系
102
In recent years, environmental sound recognition has become a new research topic in home automation. In home automation systems, the sound recognized by the system becomes the basis for performing certain tasks. However, there are various disturbances which may cause recognition system to fail in real world applications. For example, a target source is mixed with another sound due to simultaneous occurrence, or the sound received by the applications is exposed to background noise. To resolve these two issues, we totally propose three robust processing methods in this dissertation. We firstly propose a mixed sound verification method to deal with simultaneous occurrence of sounds. For the problem of background noise, this dissertation adopts two approaches to reduce the impact on recognition. The first approach is sound enhancement, which suppresses the noise of received sound before feature extraction. The second approach is to simultaneously remove noise and extract feature (implements feature extraction and denoising simultaneously), called robust feature extraction. To handle the problem of simultaneous occurrences of multiple sounds, this study proposes a framework, which consists of sound separation and sound verification techniques based on a wireless sensor network (WSN). For the problem of reducing noice from the input audio, we propose a fast subspace based sound enhancement method to filter background noise on signal subspace. For the approach of robust feature extraction, we proposed a novel feature extraction approach called nonuniform scale-frequency map for environmental sound recognition. Furthermore, the experimental results demonstrate the robustness and feasibility of the three proposed systems are superior to baseline systems.

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Tseng, Yu-Hao, e 曾郁豪. "Parallel Capsule Neural Networks for Sound Event Detection". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/33jxk4.

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碩士
國立中央大學
通訊工程學系
107
The research of artificial intelligence has never stopped for more than 60 years. With the rapid development of technology, we hope that computers can have the same learning ability as human beings. In recent years, more and more people invest in the field of machine learning and deep learning, because of the success of the alpha go. Many different network architectures have been developed to allow computers to assist humans in detecting and classifying data. We used the Capsule Neural Network (CapsNets) in deep learning as a method. Propose a system for sound event detection. The extracted features are sent to the neural network for training through the vector. In addition to capsule network can effectively identify overlapping events, we expand the capsule network into a parallel capsule network, let per capsule can learn more features. Compared with DCASE 2017 Baseline, our proposed method error rate is reduced by about 41%. Compared with the architecture of the first place in DCASE 2017 challenge, the error rate also dropped by about 26%.

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Galileu, João Pedro Duarte. "Urban Sound Event Classification for Audio-Based Surveillance Systems". Master's thesis, 2020. https://hdl.handle.net/10216/126838.

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Galileu, João Pedro Duarte. "Urban Sound Event Classification for Audio-Based Surveillance Systems". Dissertação, 2020. https://hdl.handle.net/10216/126838.

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Liao, Jyun-Ci, e 廖俊祺. "Environmental Sound Event Classification Based on Modulation Spectral Vectors". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/77th6k.

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碩士
國立清華大學
電機工程學系所
105
The Gaussian mixture model (GMM) has developed well both in the speech and sound recognition, but it does not perform well in the high background noisy environment. This thesis proposes a method combining short-term and long-term features to overcome this issue. Here the short-term features are Mel-frequency cepstral coefficients (MFCCs) and the long-term features are the modulation spectral vectors (MSVs) calculated in the frequency domain. The MSVs contains the envelope message of signals which is a good feature against high noise. For robustness against noise, this thesis proposes a method to learn noisy data while training on GMMs. This method could raise the recognition accuracy in the low singal-to-noise ratio (SNR) case. The method was evaluated on a database which consists of 8 different indoor sound event classes. It achieves > 80 % accuracy at 0 dB SNR.

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Chou, Szu-Yu, e 周思瑜. "Attention-based Sound Event Recognition using Weakly Labeled Data". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/cfexpb.

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博士
國立臺灣大學
資訊網路與多媒體研究所
107
Understanding the surrounding environment and ongoing events through acoustic cues, or the so-called ``sound intelligence,'' is a critical piece of the Artificial Intelligence (AI) puzzle. Human is able to recognize not only the sounds of speech utterance or musical piece, but also animal sounds, natural sounds and common everyday environmental sounds. With sound intelligence, an AI can do much better in applications such as smart surveillance, smart city, smart car, and smart factory. As a result, recent years have witnessed great and rapid progress in recognizing various sound events in daily environments. Most current research proposes a framework based on fully-supervised deep learning techniques using strongly labeled data. However, the labeled data for sound event recognition generally lack detailed annotations in time due to the high cost of the labeling process. This dissertation makes the following four contributions in recognizing sound events using weakly labeled data. First, we propose an attention-based model that recognizes transient sound events relying on only weakly labeled data. This task is challenging because weakly labeled data only provide annotations on the clip level, but some sound events appear only for a short period of time in an audio clip. We address this lack of detailed annotations with a novel attentional supervision mechanism that we propose. The resulting model, dubbed the M&mnet, outperforms all the other existing models on AudioSet, a collection of two million weakly-labeled audio clips released by Google in 2017. Second, we address the challenge to recognize sound events with only a few training examples of each class. This problem is critical in that fully-supervised learning algorithms cannot learn well when the data is sparse. We propose a novel attentional similarity module to guide the learning model to pay attention to specific segments of a long audio clip for recognizing sound events. We show that this module greatly improves the performance of few-shot sound recognition. Third, we propose FrameCNN, a novel weakly-supervised learning framework that improves the performance of convolutional neural network (CNN) for acoustic event detection by attending to details of each sound at various temporal levels. In the large-scale weakly supervised sound event detection for smart cars , we obtained a F-score 53.8% for sound event audio tagging, compared to the baseline of 19.8%, and a F-score 32.8% for sound event detection, compared to the baseline of 11.4%. Lastly, we attempt to build a noise-robust sound event detection model for mobile or embedded applications. We desire the model to be applicable in a real-world environment, with low memory usage and limited detection latency. By combining several state-of-the-art techniques in building deep learning models, we are able to implement a baby cry detector on the Raspberry Pi that can run in real time. We find that our model can effectively detect baby cries in various noisy conditions, whereas the baby cry detector available on the flagship smartphone of Samsung (as of late 2018) cannot.

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Liu, Chen-Hung, e 劉振宏. "A Deep Neural Network for Sound Event Recognition Implemented in Microcontroller". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3zf6sx.

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碩士
國立中央大學
資訊工程學系在職專班
107
Typical deep neural networks require the use of considerable memories and high-speed floating-point arithmetic; hence, it is difficult to apply it to microcontroller-embedded platforms with limited hardware resources. Deep neural networks can be successfully applied in recognizing sound events. To facilitate the implementation of microcontroller platforms in deep sound event recognition, this study proposed a quantization strategy to compress deep neural networks and optimize the recognition performance and hardware resource needs. This study adopted the depthwise separable convolutional neural network (DS-CNN) structure to establish the neural network model for sound event recognition. Mel-frequency cepstral coefficients (MFCC) that extract sound were used as the features to train recognition models. Through the quantization process, the quantized weight parameters were input into an ARM Cortex-M7 microcontroller to facilitate verification. The neural network model that completed training on a personal computer platform reached a recognition rate of 82%. After the model was quantized and transferred to a microcontroller unit, the recognition rate dropped to 60% with the recognition speed remaining at 0.2 second. The result verified that the proposed method can enable the deep neural network model training on a personal computer to be transferred to microcontroller units while maintaining acceptable recognition performance and recognition rates. The results can extend the deep learning artificial intelligence technologies to numerous applications with low requirement of hardware resources.

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Kogeler, Konstantin Friedrich. "Business adaptive strategies in crises : the impact of the Corona Crisis on Crystal Sound an Event Technology Provider". Master's thesis, 2021. http://hdl.handle.net/10400.14/35171.

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The COVID-19 pandemic has a significant impact on the event sector. Large events are fully prohibited in Germany since March 2020. Crystal Sound, as a provider of event technology, had to adjust its operations as well as its strategy to the changed external environment. To compensate this decline in sales, Crystal Sound cut costs. Furthermore, Crystal Sound launched together with competitors a new legal entity to organize events for visitors in cars. This vertical integration shifted Crystal Sound from a pure service provider to a more forward integrated organizer of events. This strategic alliance enabled to achieve a regional monopoly leading to enforcing higher prices and generating higher profits. In addition, Crystal Sound shifted its focus more towards innovative digital solutions, e.g. streaming of events. However, these adjustments did not suffice to achieve break-even. Therefore, Crystal Sound decided to sell a portion of its non-current assets to disclose hidden assets to retain a positive equity-ratio. In the fiscal year 2021, Crystal Sound will generate probably again a loss. The management has to decide whether to compensate the loss by injecting additional equity or by raising additional loans. This dissertation shows how an enterprise is able to respond very quickly to significant changes in the external environment. Adjustments in the product portfolio, vertical integration, collusion with competitors, disclosing hidden reserves of the balance sheet, and tremendous cost-cutting enabled that Crystal Sound generated a profit in the fiscal year 2020 despite the pandemic and massive reduction in revenue from traditional customers.
A pandemia COVID-19 tem um impacto significativo no setor de eventos. Grandes eventos estão totalmente proibidos na Alemanha desde março de 2020. A Crystal Sound, fornecedora de tecnologia de eventos, teve que ajustar as suas operações, bem como a sua estratégia ao ambiente externo alterado. Para compensar a queda nas vendas, a Crystal Sound cortou custos. Além disso, a Crystal Sound lançou com concorrentes uma entidade legal para organizar eventos disponíveis a partir de carros. Essa integração vertical mudou a Crystal Sound de fornecedor de serviços puro para um organizador integrado de eventos sofistifcados. Esta aliança estratégica alcançou um monopólio regional, permitindo preços mais altos e à geração de alguns ganhos. Além disso, o Crystal Sound mudou seu foco para soluções digitais como streaming de eventos. No entanto, esses ajustes não foram suficientes para o breakeven. Portanto, a Crystal Sound decidiu vender alguns dos ativos não-correntes para contabilizar ativos antes ausentes e equilibrar o balanço. No ano de 2021, o Crystal Sound gerará novamente um prejuízo. A administração deve decidir se compensa a perda injetando capital ou levantando empréstimos adicionais. Esta dissertação mostra como uma empresa é capaz de responder rapidamente a mudanças significativas no ambiente externo. Ajustes no portfólio de produtos, integração vertical, conluio com concorrentes, revelação de reservas ocultas do balanço patrimonial e enorme corte de custos permitiram que a Crystal Sound gerasse lucro no ano de 2020, apesar da pandemia e da redução maciça na receita de clientes tradicionais.

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Hou, Shih Yen, e 侯詩彥. "Sound Event Detection Using Different Feature Extraction and Multi-label Classification Methods". Thesis, 2017. http://ndltd.ncl.edu.tw/handle/t4tvf9.

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碩士
國立清華大學
電機工程學系
105
Events occur simultaneously at some scenes. The ability that people are able to detect these events and analyse these scenes by listening is called auditory scene analysis, and the study to let computers have this ability is called computational auditory scene analysis. Sound event detection is a topic that relates to computational auditory scene analysis, which focuses on converting acoustic signal to concrete descriptions of its corresponding sound events. This technology can be used in many applications, such as house security, healthcare, and so on. Through methods developed in pattern recognition, acoustic signal can be turned into feature vectors first, then learning methods can be applied to train models with these feature vectors and their corresponding event labels. Since the data used here were recorded in environments with multiple sound sources, polyphonic sound event detection is required such that the system can detect multiple events at the same time. Compared to monophonic sound event detection, polyphonic sound event detection is more complicated and can be viewed as multi-label classification. This research used TUT Sound Events 2016 database, which was published by Detection and Classification of Acoustic Scenes and Events 2016 (DCASE 2016). The baseline system of the database used mel frequency cepstral coefficients for feature extraction and Gaussian mixture models for multi-label classification. This paper tries to improve the performance by introducing another feature extraction method based on a human auditory model and multi-label classification methods based on deep neural networks. After trying different combination of feature extraction method and multi-label classification methods, the proposed method reduces the error rate by 0.04 and increases the F-score by 6.6% compared to baseline.

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Huang, Jong-Yi, e 黃仲逸. "Artificial intelligence (AI) sound event classification based on deep neural networks (DNNs)". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/asqgqh.

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Wang, Chun-Hao, e 王君豪. "Sound Event Detection Based on Partitioned Autoencoder and Convolutional Recurrent Neural Network". Thesis, 2018. http://ndltd.ncl.edu.tw/handle/7rna2b.

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碩士
國立清華大學
電機工程學系
107
In this thesis, a noise reduction process and a sound event detection (SED) system are used in detecting DCASE2017 TUT Sound Events 2017 dataset [1] which contains six sound events in a total of 32 audio recordings (24 audio recordings in the development set and 8 audio recordings in the evaluation set). It is a polyphonic task and the trained SED model have to detect the sound events with their onset time and offset time. The purpose of the noise reduction is to observe whether it is helpful in the training process of the sound event detection task. In this thesis, a partitioned autoencoder [2] is adopted for noise reduction. In the sound event detection part, a convolutional recurrent neural network (CRNN) [3][4] which won the first prize in the task of "sound event detection in real life" in DCASE2017 is adopted. The original log mel-band energies, the denoised log mel-band energies, and the augmented log mel-band energies which combine both of above are the input features of the CRNN. From the training results, it reveals that the SED models trained with the denoised features have better performance in some sound events by showing the lower medians of the testing error rates or showing the better distribution of the testing error rates. Furthermore, the final performance of the error rates reveals that the models trained with the denoised features can achieve the best testing error rate of 0.622 in the development set and the best testing error rate of 0.744 in the evaluation set. The testing error rate could be improved further if choosing the best model of each class across 3 kinds of features.

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Cervantes, Gamboa Laura. "Sounds like music ritual speech events among the Bribri Indians of Costa Rica /". 2003. http://wwwlib.umi.com/cr/utexas/fullcit?p3110754.

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Engelbrecht, B. J. "Sound art in Johannesburg: a critical review 2005-2009". Thesis, 2010. http://hdl.handle.net/10539/8228.

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ABSTRACT In this dissertation I offer a critical review of ‘sound art’ in Johannesburg between 2005 and 2009. The term ‘sound art’ was coined by Dan Lander in 1989. According to Christoph Cox, Dan Lander’s lament that sound art lacked “any substantial discourse” in 1989 still applied in 2007. My intention in this research is to start such a critical discourse for sound art in Johannesburg. I argue that sound art is a distinctive practice in the city, involving the body politic and underground, surface and edge as characterised by Achille Mbembe and Sarah Nuttall in their recent major work on Johannesburg. First I briefly consider the history of sound art, referring to Brandon Labelle’s view that this history parallels that of site-specific art. I then suggest that the popularity of sound art under review became popular for a number of reasons; what Walter Ong’s termed “a shift in the sensorium”, the immediacy and inexpensiveness of working with sound, and the rise of the home computer. I also locate the sonic practices constituting sound art in audio culture as a whole, focussing on the structure, materiality, recording, playback and transmission of the sonic event in the sonic landscape. Sound, silence, noise and music are all part of this focus. I finally examine sound in terms of space, time, body and network in the work of Frances Goodman, Siobhan McCusker, The Trinity Session, Teamuncool, Gerhard Marx and my own sound work involving sampling, Happy Station (2008) and Slice Me Nice (2009).

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Liao, Wei-Chung, e 廖唯鈞. "Joint Kernel Dictionary Learning via Collaborative Representation and Its Application to Sound Event Classification". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/4srjsy.

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碩士
國立中央大學
資訊工程學系
102
Environment sound classification is become more and more popular in humans daily life, such as security surveillance, environment detection, human health care. To accurately classify the sound from different event, we can use the traditional SVM, GMM and the popular SRC to obtain well classification result. In this paper, we present a joint kernel dictionary learning (JKDL) method base on sparse representation. Using ℓ2-norm instead of ℓ1-norm can reserve the performance but reduce the computation time massively. Adding the classification error term into the objective function to train a simple linear classifier enhanced the relationship between the classifier and dictionary. Kernel method plays an important role which efficiently strengthen the reconstructive and discriminative ability. The dictionary update step is iteratively performed by taking partial derivatives on objective function in feature space. Online dictionary learning approach handle dynamic training data more efficient than batch approach. Experiments on a 17 classes sound database indicates that the proposed method can achieve an high accuracy rate about 80.56%. Also, the average executing time of a testing data is notably faster than SRC and CRC.

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Cornell, Sonia [Verfasser]. "Mapping speech sound to mental representation : neurophonological evidence from event-related brain potentials / vorgelegt von Sonia Cornell". 2010. http://d-nb.info/1010932861/34.

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Monteiro, Bruno Daniel Gonçalves. "Eventos culturais como ferramenta de gestão para o turismo em Portugal : estudo de caso NOS Primavera Sound 2013 e 2014". Master's thesis, 2014. http://hdl.handle.net/11067/1977.

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Exame público realizado em 19 Janeiro 2015.
Dissertação de mestrado realizada no âmbito do Mestrado em Gestão.
A celebração de eventos culturais pode desempenhar vários papéis importantes, que vão desde a atração de turistas, à animação que se prolonga no tempo, à dinamização de outras atividades, até a elemento de suporte à criação de uma imagem do destino turístico. Deste modo, a multiplicação de eventos culturais, nomeadamente festivais, promove um impacto no turismo nas empresas dos diferentes serviços da região destino, o que tem consequentemente reflexos ao nível do emprego e no consumo. Verificando a elevada concorrência entre o turismo de cidades e os eventos culturais, tornou-se importante determinar o impacto direto da gestão do evento, bem como na cidade onde este se realiza (como por exemplo, o impacto no alojamento, nas deslocações, nas compras/presentes, cultura tura/lazer e no recinto), o impacto induzido (considerando os gastos nas refeições) e os principais fatores de satisfação juntamente com a possibilidade de retorno. Nesta dissertação avaliam-se os principais determinantes dos dois tipos diferentes de comportamento das despesas dos turistas num festival de música: as despesas por dia na cidade do evento e as despesas no próprio recinto durante o evento. Ao nível da satisfação dos visitantes, além de se verificar que os visitantes mais satisfeitos gastaram mais no recinto do evento, verificou-se também que os principais fatores foram agrupados nos palcos de música, na duração do festival e horário dos concertos, nas condições do recinto, nos restaurantes e sanitários e no mercado Primavera. Ou seja, no caso em estudo, estes fatores revelaram-se decisivos para a escolha do evento. Provamos que os turistas que se deslocaram propositadamente para o evento e os estrangeiros gastam mais por dia no recinto, enquanto relativamente aos gastos na cidade, os estrangeiros gastam mais do que os cidadãos nacionais. Estes resultados indicam que a residência dos turistas tem um impacto positivo nos gastos. Ficou ainda demonstrado que as despesas na cidade durante o festival são determinadas pela idade, estado civil, escolaridade, rendimento e nacionalidade do turista, enquanto as despesas no próprio recinto do evento são explicadas pelo género, idade, rendimento, nacionalidade, ano de realização, vinda propositada para o evento e tipo de bilhete adquirido. Este tipo de informações são uma importante ferramenta de gestão para o turismo local e para a decisão do desempenho e planeamento do evento. O turismo local pode não só concentrar em atrair turistas, mas também em fazer o evento se tornar memorável em cooperação com a empresa do evento.
Abstract: There are numerous important roles that can be found in the celebration of cultural events. These go from tourist attraction to the animation of attractions that are repeated, mostly on an annual basis, amplification of several other side-activities or the becoming of a supporting element for the creation of a certain touristic destination’s widespread image. This way, the spread of said cultural events, like music festivals, and the legions of tourists it attracts, cause a considerably big impact on the cities and regions where these festivals are held, on businesses from different sectors. All of this cause visible reflections on the city/region’s jobs and economy. If one takes into account the high competition present within cities between the tourism and their cultural events, determining the direct impact from the event’s management has become important, as well as taking into account the city where it takes place (for example: the impact on accommodation, dislocations, shopping, culture and leisure and the very festival grounds), the induced impact (considering what’s spent on meals) and the main factors of satisfaction as well as the possibility of people wanting to return. In this essay, we will take a look at and evaluate the main factors which determine the two different types of behavior regarding expenses tourists have on a music festival: These are analyzed per day, in the city where the event takes place and the expenses in the festival grounds, during the realization of the event. Regarding the satisfaction of those who come to the events, and going beyond the realization that the most satisfied visitors have spent more money in the festival grounds, it was also verified that the items loaded on the factors were focused mainly on the stages, duration of the festival and concert schedules, conditions of the area, restaurants and sanitaria as well as the “Primavera” market. This means that, in the case of study, said factors have proven themselves as decisive towards the choice of going to the event. It has been proven that tourists who allocated themselves to the event on purpose do spend more money each day on the festival grounds, while, regarding the expenses at city level, foreigners spend more than national citizens. These results indicate the visit of these tourists has a positive impact on spends. Furthermore, it was demonstrated that the expenses on city level, during the days in which the festival is held, are determined mostly by the tourists’ age, marital status, scholarship, yield and nationality, while expenses on the festival grounds are determined mainly by gender, age, yield, nationality, current year, specific attending of the event and type of ticket acquired. In conclusion, this type of information is an important management tool for local tourism, as well as decisions regarding the performance and planning of events. Local tourism may concentrate not only on attracting tourists, but also on seeing the event becomes memorable, cooperating with the company that promotes/organizes the event.

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