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Literatura académica sobre el tema "Sound data"

Autor: Grafiati

Publicado: 4 de junio de 2021

Última modificación: 20 de febrero de 2023

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Artículos de revistas sobre el tema "Sound data"

1

NARA, SHIGETOSHI, NAOYA ABE, MASATO WADA y JOUSUKE KUROIWA. "A NOVEL METHOD OF SOUND DATA DESCRIPTION BY MEANS OF CELLULAR AUTOMATA AND ITS APPLICATION TO DATA COMPRESSION". International Journal of Bifurcation and Chaos 09, n.º 06 (junio de 1999): 1211–17. http://dx.doi.org/10.1142/s0218127499000869.

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A novel method of binary data description using cellular automata is proposed. As an actual example, several trials are made to describe vocal and musical sound data digitized in a standard data format. The reproduced sounds are evaluated by "actual listening", by calculating "the signal to noise ratio" with respect to the original sound data, and by comparing "the Fourier power spectra" with those of the original sounds. The results show that this method is quite effective and provides a new means of data compression applicable in any field of digital data recording or transferring.

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BAKIR, Çiğdem. "Compressing English Speech Data with Hybrid Methods without Data Loss". International Journal of Applied Mathematics Electronics and Computers 10, n.º 3 (30 de septiembre de 2022): 68–75. http://dx.doi.org/10.18100/ijamec.1166951.

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Understanding the mechanism of speech formation is of great importance in the successful coding of the speech signal. It is also used for various applications, from authenticating audio files to connecting speech recording to data acquisition device (e.g. microphone). Speech coding is of vital importance in the acquisition, analysis and evaluation of sound, and in the investigation of criminal events in forensics. For the collection, processing, analysis, extraction and evaluation of speech or sounds recorded as audio files, which play an important role in crime detection, it is necessary to compress the audio without data loss. Since there are many voice changing software available today, the number of recorded speech files and their correct interpretation play an important role in detecting originality. Using various techniques such as signal processing, noise extraction, filtering on an incomprehensible speech recording, improving the speech, making them comprehensible, determining whether there is any manipulation on the speech recording, understanding whether it is original, whether various methods of addition and subtraction are used, coding of sounds, the code must be decoded and the decoded sounds must be transcribed. In this study, first of all, what sound coding is, its purposes, areas of use, classification of sound coding according to some features and techniques are given. Moreover, in our study speech coding was done on the English audio data. This dataset is the real dataset and consists of approximately 100000 voice recordings. Speech coding was done using waveform, vocoders and hybrid methods and the success of all the methods used on the system we created was measured. Hybrid models gave more successful results than others. The results obtained will set an example for our future work.

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Kim, Eunbeen, Jaeuk Moon, Jonghwa Shim y Eenjun Hwang. "DualDiscWaveGAN-Based Data Augmentation Scheme for Animal Sound Classification". Sensors 23, n.º 4 (10 de febrero de 2023): 2024. http://dx.doi.org/10.3390/s23042024.

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Animal sound classification (ASC) refers to the automatic identification of animal categories by sound, and is useful for monitoring rare or elusive wildlife. Thus far, deep-learning-based models have shown good performance in ASC when training data is sufficient, but suffer from severe performance degradation if not. Recently, generative adversarial networks (GANs) have shown the potential to solve this problem by generating virtual data. However, in a multi-class environment, existing GAN-based methods need to construct separate generative models for each class. Additionally, they only consider the waveform or spectrogram of sound, resulting in poor quality of the generated sound. To overcome these shortcomings, we propose a two-step sound augmentation scheme using a class-conditional GAN. First, common features are learned from all classes of animal sounds, and multiple classes of animal sounds are generated based on the features that consider both waveforms and spectrograms using class-conditional GAN. Second, we select data from the generated data based on the confidence of the pretrained ASC model to improve classification performance. Through experiments, we show that the proposed method improves the accuracy of the basic ASC model by up to 18.3%, which corresponds to a performance improvement of 13.4% compared to the second-best augmentation method.

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4

Han, Hong-Su. "Sound data interpolating circuit". Journal of the Acoustical Society of America 100, n.º 2 (1996): 692. http://dx.doi.org/10.1121/1.416225.

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5

Son, Myoung-Jin y Seok-Pil Lee. "COVID-19 Diagnosis from Crowdsourced Cough Sound Data". Applied Sciences 12, n.º 4 (9 de febrero de 2022): 1795. http://dx.doi.org/10.3390/app12041795.

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The highly contagious and rapidly mutating COVID-19 virus is affecting individuals worldwide. A rapid and large-scale method for COVID-19 testing is needed to prevent infection. Cough testing using AI has been shown to be potentially valuable. In this paper, we propose a COVID-19 diagnostic method based on an AI cough test. We used only crowdsourced cough sound data to distinguish between the cough sound of COVID-19-positive people and that of healthy people. First, we used the COUGHVID cough database to segment only the cough sound from the original cough data. An effective audio feature set was then extracted from the segmented cough sounds. A deep learning model was trained on the extracted feature set. The COVID-19 diagnostic system constructed using this method had a sensitivity of 93% and a specificity of 94%, and achieved better results than models trained by other existing methods.

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Yamamoto, Takaharu. "Digital sound data storing device". Journal of the Acoustical Society of America 93, n.º 1 (enero de 1993): 596. http://dx.doi.org/10.1121/1.405540.

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Osborne, D. W. "Sound and data on DBS". Electronics and Power 31, n.º 6 (1985): 449. http://dx.doi.org/10.1049/ep.1985.0283.

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8

Kaper, H. G., E. Wiebel y S. Tipei. "Data sonification and sound visualization". Computing in Science & Engineering 1, n.º 4 (1999): 48–58. http://dx.doi.org/10.1109/5992.774840.

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Suhartini, Endang, Murdianto Murdianto y Nanik Setyowati. "OPTIMALISASI PELAYANAN BINA KOMUNIKASI MELALUI PROGRAM PERSEPSI BUNYI DAN IRAMA (BKPBI), UNTUK ANAK YANG BERKEBUTUHAN KUSUS TUNARUNGGU DI SDLB NEGERI JENANGAN PONOROGO". BASICA: Journal of Arts and Science in Primary Education 1, n.º 1 (15 de mayo de 2021): 58–71. http://dx.doi.org/10.37680/basica.v1i1.777.

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Children with special needs are children with different characteristics from normal children in general. Especially deaf children are children who have impaired hearing either totally or have residual hearing. Deaf communication requires services that can support their communication difficulties. In this case SDLB Negeri Jenang Ponorogo organized a communication development program with Communication Development through the Sound and Rhythm Perception Program (BKPBI). In this study the author is intended to discuss more about; Forms of service stages, learning implementation strategies and service results of sound and rhythm perception programs in SDLB Negeri Jenang Ponorogo. This research uses a qualitative approach methodology with the type of case study research. The data in this study are words and actions, while the source of the data are the Principal and teachers at SDLB Negeri Jenang. Data collection methods are interviews, observation, and documentation. Data analysis techniques using data reduction, data presentation, and drawing conclusions. After conducting the analysis, the writer can conclude that the form of communication service development stages through sound and rhythm perception programs in the Jenang Negeri Extraordinary Elementary School is sound detection, sound discrimination, sound identification, sound comprehension, learning implementation strategies using review, overview, presentation, exercise, and summary, also by using the classical and individual models, while the results of the service program of perception of sound and rhythm in the State Elementary School Extraordinary, namely deaf children are able to recognize sounds, easy to respond to sounds such as background noises, the nature of sounds, creating sounds up to recognize types of musical instruments, able to identify sounds and detect the direction of sound.

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Roelandt, N., P. Aumond y L. Moisan. "CROWDSOURCED ACOUSTIC OPEN DATA ANALYSIS WITH FOSS4G TOOLS". International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLVIII-4/W1-2022 (6 de agosto de 2022): 387–93. http://dx.doi.org/10.5194/isprs-archives-xlviii-4-w1-2022-387-2022.

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Abstract. NoiseCapture is an Android application developed by the Gustave Eiffel University and the French National Centre for Scientific Research as central element of a participatory approach to environmental noise mapping. The application is open-source, and all its data are available freely. This study presents the results of the first exploratory analysis of 3 years of data collection through the lens of sound sources. This analysis is only based on the tags given by the users and not on the sound spectrum of the measurement, which will be studied at a later stage. The first results are encouraging, we were able to observe well known temporal sound source dynamics like road sounds temporal dynamic related to commuting or bird songs in the dataset. We also found correlations between wind and rain tags and their measurements by the the national meteorological service. The context of the study, the Free and Open Source Software tools and techniques used and literate programming benefits are presented.

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Tesis sobre el tema "Sound data"

1

Hebden, John Edward. "Acquisition and analysis of heart sound data". Thesis, University of Sussex, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.360518.

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Bearman, N. "Using sound to represent uncertainty in spatial data". Thesis, University of East Anglia, 2013. https://ueaeprints.uea.ac.uk/52676/.

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There is a limit to the amount of spatial data that can be shown visually in an effective manner, particularly when the data sets are extensive or complex. Using sound to represent some of these data (sonification) is a way of avoiding visual overload. This thesis creates a conceptual model showing how sonification can be used to represent spatial data and evaluates a number of elements within the conceptual model. These are examined in three different case studies to assess the effectiveness of the sonifications. Current methods of using sonification to represent spatial data have been restricted by the technology available and have had very limited user testing. While existing research shows that sonification can be done, it does not show whether it is an effective and useful method of representing spatial data to the end user. A number of prototypes show how spatial data can be sonified, but only a small handful of these have performed any user testing beyond the authors’ immediate colleagues (where n > 4). This thesis creates and evaluates sonification prototypes, which represent uncertainty using three different case studies of spatial data. Each case study is evaluated by a significant user group (between 45 and 71 individuals) who completed a task based evaluation with the sonification tool, as well as reporting qualitatively their views on the effectiveness and usefulness of the sonification method. For all three case studies, using sound to reinforce information shown visually results in more effective performance from the majority of the participants than traditional visual methods. Participants who were familiar with the dataset were much more effective at using the sonification than those who were not and an interactive sonification which requires significant involvement from the user was much more effective than a static sonification, which did not provide significant user engagement. Using sounds with a clear and easily understood scale (such as piano notes) was important to achieve an effective sonification. These findings are used to improve the conceptual model developed earlier in this thesis and highlight areas for future research.

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Diaz, Merced Wanda Liz. "Sound for the exploration of space physics data". Thesis, University of Glasgow, 2013. http://theses.gla.ac.uk/5804/.

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Current analysis techniques for space physics 2D numerical data are based on scruti-nising the data with the eyes. Space physics data sets acquired from the natural lab of the interstellar medium may contain events that may be masked by noise making it difficult to identify. This thesis presents research on the use of sound as an adjunct to current data visualisation techniques to explore, analyse and augment signatures in space physics data. This research presents a new sonification technique to decom-pose a space physics data set into different components (frequency, oscillatory modes, etc…) of interest, and its use as an adjunct to data visualisation to explore and analyse space science data sets which are characterised by non-linearity (a system which does not satisfy the superposition principle, or whose output is not propor-tional to its input). Integrating aspects of multisensory perceptualization, human at tention mechanisms, the question addressed by this dissertation is: Does sound used as an adjunct to current data visualisation, augment the perception of signatures in space physics data masked by noise? To answer this question, the following additional questions had to be answered: a) Is sound used as an adjunct to visualisation effective in increasing sensi-tivity to signals occurring at attended, unattended, unexpected locations, extended in space, when the occurrence of the signal is in presence of a dynamically changing competing cognitive load (noise), that makes the signal visually ambiguous? b) How can multimodal perceptualization (sound as an adjunct to visualisa-tion) and attention control mechanisms, be combined to help allocate at-tention to identify visually ambiguous signals? One aim of these questions is to investigate the effectiveness of the use of sound to-gether with visual display to increase sensitivity to signal detection in presence of visual noise in the data as compared to visual display only. Radio, particle, wave and high energy data is explored using a sonification technique developed as part of this research. The sonification technique developed as part of this research, its application and re-sults are numerically validated and presented. This thesis presents the results of three experiments and results of a training experiment. In all the 4 experiments, the volun-teers were using sound as an adjunct to data visualisation to identify changes in graphical visual and audio representations and these results are compared with those of using audio rendering only and visual rendering only. In the first experiment audio rendering did not result in significant benefits when used alone or with a visual display. With the second and third experiments, the audio as an adjunct to visual rendering became significant when a fourth cue was added to the spectra. The fourth cue con-sisted of a red line sweeping across the visual display at the rate the sound was played, to synchronise the audio and visual present. The results prove that a third congruent multimodal stimulus in synchrony with the sound helps space scientists identify events masked by noise in 2D data. Results of training experiments are reported.

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4

Durey, Adriane Swalm. "Melody spotting using hidden Markov models". Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180126/unrestricted/durey%5Fadriane%5Fs%5F200312%5Fphd.pdf.

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5

Smith, Adrian Wilfrid. "A distributed approach to surround sound production". Thesis, Rhodes University, 1999. http://hdl.handle.net/10962/d1004855.

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The requirement for multi-channel surround sound in audio production applications is growing rapidly. Audio processing in these applications can be costly, particularly in multi-channel systems. A distributed approach is proposed for the development of a realtime spatialization system for surround sound music production, using Ambisonic surround sound methods. The latency in the system is analyzed, with a focus on the audio processing and network delays, in order to ascertain the feasibility of an enhanced, distributed real-time spatialization system.

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6

Stensholt, Håkon Meyer. "Sound Meets Type : Exploring the form generating qualities of sound as input for a new typography". Thesis, Konstfack, Grafisk Design & Illustration, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:konstfack:diva-4761.

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How can you create new letterforms using sound as input? In Sound meets Type, have I studied the form generating qualities of sound as input for a new typography. Through history the technological development has provoked new approaches to type design, which in turn has evolved letterforms. By using generative systems to search for letterforms in a contemporary and technological context, I have created a customized software that uses the data inherent in sound as a form generator for possible new letterforms. The software is developed by using a language called Javascript. The thesis consist of a written part and a creative part. The creative part is documented within this thesis.

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7

Manekar, Vedang V. M. S. "Development of a Low-cost Data Acquisition System using a Sound Card". University of Cincinnati / OhioLINK, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1554121267971882.

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Berglund, Alexander, Fredrik Herbai y Jonas Wedén. "Sound Propagation Through Walls". Thesis, Uppsala universitet, Avdelningen för beräkningsvetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-444632.

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Infrasound is undetectable by the human ear and excessive exposure may be a substantial health risk. Low frequency sound propagates through walls with minimal attenuation, making it difficult to avoid. This study interprets the results from both analytical calculations and simulations of pressure waves propagating through a wall in one dimension. The wall is thin compared to the wavelength; the model implements properties of three materials commonly used in walls. The results indicate that the geometry of the wall, most importantly the small ratio between wall width and wavelength, is the prime reason for the low levels of attenuation observed in transmitted amplitudes of low frequency sounds, and that damping is negligible for infrasound. Furthermore, a one-dimensional homogeneous wall model gives rise to periodicity in the transmitted amplitude, which is not observed in experiments. Future studies should prioritize the introduction of at least one more dimension to the model, to allow for variable angles of incidence.

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9

Ashraf, Pouya. "Improving Spatial Sound Capturing on Mobile Devices Through Fusion of Inertial Measurement Data". Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-372151.

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Through the use of sensor arrays it is possible to extract spatial information about signals present in the environment. For instance position, velocity, distance, etc. In this thesis we focus on the use of microphone arrays with the aim of accurately determining, and over time track, the Direction of Arrival (DoA) of nearby sound signals impinging on the array. As modern mobile devices like smartphones and tablets are commonly equipped with two or more microphones, these constitute a simple microphone array. This gives us the opportunity of attaining the above aim. However, in the scenario that the microphone array is not stationary, a number of problems arise. In this thesis we implement an algorithm to estimate the microphone array's orientation in three-dimensional space, with the aim of using these estimates to cancel the effect of the array's orientation on the DoA estimates. The cancellation is done with a dynamical model, which we use in a modified Kalman Filter (KF) capable of tracking an arbitrary number of sound sources over time. Additionally, we estimate the computational cost of the mentioned algorithms. The simulation results show satisfactory performance in the modified KF with respect to handling crossing trajectories and noise in the measurements. The chosen algorithm for orientation estimation proves susceptible to magnetic disturbances to the extent that usage in the context of mobile devices is undesirable. Due to this, the orientation estimates are provided by a proprietary algorithm. Experiments where the DoA of the sound sources are computed using actual sound, together with orientation estimates, confirm the correctness of the proposed model.

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10

Kesterton, Anthony James. "The synthesis of sound with application in a MIDI environment". Thesis, Rhodes University, 1991. http://hdl.handle.net/10962/d1006701.

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The wide range of options for experimentation with the synthesis of sound are usually expensive, difficult to obtain, or limit the experimenter. The work described in this thesis shows how the IBM PC and software can be combined to provide a suitable platform for experimentation with different synthesis techniques. This platform is based on the PC, the Musical Instrument Digital Interface (MIDI) and a musical instrument called a digital sampler. The fundamental concepts of sound are described, with reference to digital sound reproduction. A number of synthesis techniques are described. These are evaluated according to the criteria of generality, efficiency and control. The techniques discussed are additive synthesis, frequency modulation synthesis, subtractive synthesis, granular synthesis, resynthesis, wavetable synthesis, and sampling. Spiral synthesis, physical modelling, waveshaping and spectral interpolation are discussed briefly. The Musical Instrument Digital Interface is a standard method of connecting digital musical instruments together. It is the MIDI standard and equipment conforming to that standard that makes this implementation of synthesis techniques possible. As a demonstration of the PC platform, additive synthesis, frequency modulation synthesis, granular synthesis and spiral synthesis have been implemented in software. A PC equipped with a MIDI interface card is used to perform the synthesis. The MIDI protocol is used to transmit the resultant sound to a digital sampler. The INMOS transputer is used as an accelerator, as the calculation of a waveform using software is a computational intensive process. It is concluded that sound synthesis can be performed successfully using a PC and the appropriate software, and utilizing the facilities provided by a MIDI environment including a digital sampler.

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Libros sobre el tema "Sound data"

1

The Sound on sound book of MIDI for the technophobe. London: Sanctuary Publishing, 1997.

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Yavelow, Christopher. Macworldmusic & sound bible. San Mateo, Calif: IDG Books, 1992.

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1963-, Miranda Eduardo Reck, ed. Computer sound design: Synthesis techniques and programming. 2^a ed. Boston, Mass: Focal Press, 2002.

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Semiconductors, ITT. MSP 3410D: Multistandard sound processor : preliminary data sheet. Freiburg: ITT Semiconductors, 1997.

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The sound on sound book of live sound for the performing musician. London: Sanctuary Publishing, 1998.

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Semiconductors, ITT. MSP 3400 C: Multistandard sound processor : preliminary data sheet. Freiburg: ITT Semiconductors, 1995.

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7

E, Ffowcs Williams John, Schultz Martin H, Pierce Allan D y Lee Ding 1925-, eds. International Conference on Theoretical and Computational Acoustics: Mystic Hilton, Mystic, Connecticut, USA, 5-9 July 1993. Singapore: World Scientific, 1994.

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8

Media composer 6: Professional picture and sound editing. Boston, MA: Course Technology, Cengage Learning, 2013.

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9

Computational atmospheric acoustics. Dordrecht: Kluwer Academic Publishers, 2001.

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Macworld music & sound bible. San Mateo, Calif: IDG Books, 1992.

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Capítulos de libros sobre el tema "Sound data"

1

Eargle, John M. "Sound Pressure and dB Lp (Sound Pressure Level)". En Electroacoustical Reference Data, 2–3. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2027-6_1.

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Rumsey, Francis y Tim McCormick. "Audio Data Reduction". En Sound and Recording, 295–318. 8^a ed. New York: Routledge, 2021. http://dx.doi.org/10.4324/9781003092919-9.

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Eargle, John M. "Fresnel Diffraction Over Sound Barriers". En Electroacoustical Reference Data, 32–33. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2027-6_16.

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Eargle, John M. "Sound Transmission Class (STC) Curves". En Electroacoustical Reference Data, 18–19. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2027-6_9.

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Anand, S. Abhishek y Nitesh Saxena. "A Sound for a Sound: Mitigating Acoustic Side Channel Attacks on Password Keystrokes with Active Sounds". En Financial Cryptography and Data Security, 346–64. Berlin, Heidelberg: Springer Berlin Heidelberg, 2017. http://dx.doi.org/10.1007/978-3-662-54970-4_21.

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Lee, Ook. "Mobile Data Management with Sound". En Advances in Web-Age Information Management, 610–15. Berlin, Heidelberg: Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-540-27772-9_61.

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Eargle, John M. "Sound Attenuation over Distance in Semireverberant Spaces". En Electroacoustical Reference Data, 44–45. Boston, MA: Springer US, 1994. http://dx.doi.org/10.1007/978-1-4615-2027-6_22.

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Smith, Leslie S. "Data-driven Sound Interpretation: its Application to Voiced Sounds". En Workshops in Computing, 147–54. London: Springer London, 1995. http://dx.doi.org/10.1007/978-1-4471-3579-1_12.

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Glattetre, John. "Some Aspects of Sound Propagation in Shallow Water: Estimation of Source- and Sound Chanel Parameters". En Underwater Acoustic Data Processing, 125–40. Dordrecht: Springer Netherlands, 1989. http://dx.doi.org/10.1007/978-94-009-2289-1_13.

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Last, Mark y Anna Usyskin. "Listen to the Sound of Data". En Multimedia Data Mining and Analytics, 419–46. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-14998-1_19.

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Actas de conferencias sobre el tema "Sound data"

1

Dover, Ian, Jawad Almaatouk, Chad Baker y John Ventura. "Data-Over-Sound Robot". En International Engineering Science Technology Online Conference. CLOUD PUBLICATIONS, 2020. http://dx.doi.org/10.23953/cloud.iestoc.468.

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Faudemay, Pascal, Claude Montacie y Marie-Jose Caraty. "Video indexing based on image and sound". En Voice, Video, and Data Communications, editado por C. C. Jay Kuo, Shih-Fu Chang y Venkat N. Gudivada. SPIE, 1997. http://dx.doi.org/10.1117/12.290365.

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Krekovic, Miranda, Gilles Baechler, Ivan Dokmanic y Martin Vetterli. "Structure from Sound with Incomplete Data". En ICASSP 2018 - 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2018. http://dx.doi.org/10.1109/icassp.2018.8462559.

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Dindar, Halil Ozgen y Gokhan Dalkilic. "Indoor Event Detection with Sound Data". En 2021 Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE, 2021. http://dx.doi.org/10.1109/asyu52992.2021.9599045.

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Martens, Susanne, Tobias Bohne y Raimund Rolfes. "An evaluation method for extensive wind turbine sound measurement data and its application". En 18th International Symposium on Long Range Sound Propagation. ASA, 2020. http://dx.doi.org/10.1121/2.0001326.

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Hämäläinen, Wilhelmiina y Geoffrey I. Webb. "Statistically sound pattern discovery". En KDD '14: The 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. New York, NY, USA: ACM, 2014. http://dx.doi.org/10.1145/2623330.2630812.

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Hermann, Thomas y Marian Weger. "Data-driven Auditory Contrast Enhancement for Everyday Sounds and Sonifications". En ICAD 2019: The 25th International Conference on Auditory Display. Newcastle upon Tyne, United Kingdom: Department of Computer and Information Sciences, Northumbria University, 2019. http://dx.doi.org/10.21785/icad2019.005.

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We introduce Auditory Contrast Enhancement (ACE) as a technique to enhance sounds at hand of a given collection of sound or sonification examples that belong to different classes, such as sounds of machines with and without a certain malfunction, or medical data sonifications for different pathologies/conditions. A frequent use case in inductive data mining is the discovery of patterns in which such groups can be discerned, to guide subsequent paths for modelling and feature extraction. ACE provides researchers with a set of methods to render focussed auditory perspectives that accentuate inter-group differences and in turn also enhance the intra-group similarity, i.e. it warps sounds so that our human built-in metrics for assessing differences between sounds is better aligned to systematic differences between sounds belonging to different classes. We unfold and detail the concept along three different lines: temporal, spectral and spectrotemporal auditory contrast enhancement and we demonstrate their performance at hand of given sound and sonification collections.

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8

Deng, Shuhao y Changchun Bao. "DNN-based Multi-Channel Speech Coding Employing Sound Localization". En 2022 Data Compression Conference (DCC). IEEE, 2022. http://dx.doi.org/10.1109/dcc52660.2022.00062.

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9

Fayek, Haytham M. y Anurag Kumar. "Large Scale Audiovisual Learning of Sounds with Weakly Labeled Data". En Twenty-Ninth International Joint Conference on Artificial Intelligence and Seventeenth Pacific Rim International Conference on Artificial Intelligence {IJCAI-PRICAI-20}. California: International Joint Conferences on Artificial Intelligence Organization, 2020. http://dx.doi.org/10.24963/ijcai.2020/78.

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Recognizing sounds is a key aspect of computational audio scene analysis and machine perception. In this paper, we advocate that sound recognition is inherently a multi-modal audiovisual task in that it is easier to differentiate sounds using both the audio and visual modalities as opposed to one or the other. We present an audiovisual fusion model that learns to recognize sounds from weakly labeled video recordings. The proposed fusion model utilizes an attention mechanism to dynamically combine the outputs of the individual audio and visual models. Experiments on the large scale sound events dataset, AudioSet, demonstrate the efficacy of the proposed model, which outperforms the single-modal models, and state-of-the-art fusion and multi-modal models. We achieve a mean Average Precision (mAP) of 46.16 on Audioset, outperforming prior state of the art by approximately +4.35 mAP (relative: 10.4%).

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Kim, Soohyun, Hyunsu Mun y Youngseok Lee. "A Data-Over-Sound Application: Attendance Book". En 2019 20th Asia-Pacific Network Operations and Management Symposium (APNOMS). IEEE, 2019. http://dx.doi.org/10.23919/apnoms.2019.8892996.

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Informes sobre el tema "Sound data"

1

Berman, David H. Sound Speed Profiles from Vertical Array Data. Fort Belvoir, VA: Defense Technical Information Center, marzo de 1994. http://dx.doi.org/10.21236/ada283978.

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Berman, David H. Sound Speed Profiles from Vertical Array Data. Fort Belvoir, VA: Defense Technical Information Center, junio de 1993. http://dx.doi.org/10.21236/ada267300.

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Fagerburg, Timothy L., Clara J. Coleman, Joseph W. Parman y George M. Fisackerly. Cumberland Sound Monitoring. Report 2. 1989 Data Collection Report. Fort Belvoir, VA: Defense Technical Information Center, agosto de 1991. http://dx.doi.org/10.21236/ada241238.

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Sherin, A. G., I. A. Hardy, S. Merchant, D. E. Beaver, D. Holt y M. Cash. A 35 mm microfilm compilation of collected bathymetry data from Cruise 77024, Labrador Sea, Davis Strait, Baffin Bay, Lancaster Sound, Jones Sound and Smith Sound, eastern Arctic. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1989. http://dx.doi.org/10.4095/130844.

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5

Younglove, B. A., N. V. Frederick y R. D. McCarty. Speed of sound data and related models for mixtures of natural gas constituents. Gaithersburg, MD: National Institute of Standards and Technology, 1993. http://dx.doi.org/10.6028/nist.mono.178.

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Sedore, P., A. Normandeau, V. Maselli y K. Regular. Bathymetry of Pangnirtung Fiord, Cumberland Sound, Nunavut. Natural Resources Canada/CMSS/Information Management, 2022. http://dx.doi.org/10.4095/329614.

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This map depicts the multibeam bathymetry data acquired in September 2019 onboard the R/V Nuliajuk in Pangnirtung Fiord, Cumberland Sound. The mapped area extends from the head of the fiord, where the Weasel River drains the surrounding highlands, to Cumberland Sound. The Hamlet of Pangnirtung rests on the SE shore of Pangnirtung Fiord. Glacial landforms and modern sediment processes are identified throughout the fiord using sub-bottom profiles and multibeam bathymetry.

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7

Ricketts, B. D. y D. J. McIntyre. The Eureka Sound Group of eastern Axel Heiberg Island: New Data On the Eurekan Orogeny. Natural Resources Canada/ESS/Scientific and Technical Publishing Services, 1986. http://dx.doi.org/10.4095/120786.

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Ferguson, Matthew y Marin Kress. AIS data case study : dredge material placement site evaluation in Frederick Sound near Petersburg, Alaska. Engineer Research and Development Center (U.S.), mayo de 2022. http://dx.doi.org/10.21079/11681/44141.

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The purpose of this Coastal and Hydraulics Laboratory Technical Note (CHETN) is to present an application of historic vessel position information acquired through the Automatic Identification System (AIS), which provides geo-referenced and time-stamped vessel position information. The US Army Corps of Engineers, Alaska District (POA), needed to evaluate potential placement sites for dredged material near Petersburg, AK, and possible impacts to navigation were considered as part of the evaluation process.

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9

Job, Jacob. Mesa Verde National Park: Acoustic monitoring report. National Park Service, julio de 2021. http://dx.doi.org/10.36967/nrr-2286703.

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In 2015, the Natural Sounds and Night Skies Division (NSNSD) received a request to collect baseline acoustical data at Mesa Verde National Park (MEVE). Between July and August 2015, as well as February and March 2016, three acoustical monitoring systems were deployed throughout the park, however one site (MEVE002) stopped recording after a couple days during the summer due to wildlife interference. The goal of the study was to establish a baseline soundscape inventory of backcountry and frontcountry sites within the park. This inventory will be used to establish indicators and thresholds of soundscape quality that will support the park and NSNSD in developing a comprehensive approach to protecting the acoustic environment through soundscape management planning. Additionally, results of this study will help the park identify major sources of noise within the park, as well as provide a baseline understanding of the acoustical environment as a whole for use in potential future comparative studies. In this deployment, sound pressure level (SPL) was measured continuously every second by a calibrated sound level meter. Other equipment included an anemometer to collect wind speed and a digital audio recorder collecting continuous recordings to document sound sources. In this document, “sound pressure level” refers to broadband (12.5 Hz–20 kHz), A-weighted, 1-second time averaged sound level (LAeq, 1s), and hereafter referred to as “sound level.” Sound levels are measured on a logarithmic scale relative to the reference sound pressure for atmospheric sources, 20 μPa. The logarithmic scale is a useful way to express the wide range of sound pressures perceived by the human ear. Sound levels are reported in decibels (dB). A-weighting is applied to sound levels in order to account for the response of the human ear (Harris, 1998). To approximate human hearing sensitivity, A-weighting discounts sounds below 1 kHz and above 6 kHz. Trained technicians calculated time audible metrics after monitoring was complete. See Methods section for protocol details, equipment specifications, and metric calculations. Median existing (LA50) and natural ambient (LAnat) metrics are also reported for daytime (7:00–19:00) and nighttime (19:00–7:00). Prominent noise sources at the two backcountry sites (MEVE001 and MEVE002) included vehicles and aircraft, while building and vehicle predominated at the frontcountry site (MEVE003). Table 1 displays time audible values for each of these noise sources during the monitoring period, as well as ambient sound levels. In determining the current conditions of an acoustical environment, it is informative to examine how often sound levels exceed certain values. Table 2 reports the percent of time that measured levels at the three monitoring locations were above four key values.

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Chamberlain, C. A. y K. Lochhead. Data modeling as applied to surveying and mapping data. Natural Resources Canada/CMSS/Information Management, 1988. http://dx.doi.org/10.4095/331263.

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The Geodetic Survey Division of the Canada Centre for Surveying is replacing the National Geodetic Data Base (NGDB) with the National Geodetic Information System (NGIS). For the NGIS to be successful, it was recognized that a sound, well engineered data mode was essential. The methodology chosen to design the data mode! was Nijssen's Information Analysis Methodology (NIAM), a binary modeling technique that is supported by a Computer Aided Software Engineering (CASE) tool, PC-IAST. An NGIS prototype has also been developed using Digital Equipment of Canada's Relational Database (Rdb) management system and COGNOS Corporations POWERHOUSE 4th generation language. This paper addresses the need for, and the advantages of using a strong engineering approach to data modeling and describes the use of the NIAM methodology in NGIS development. The paper identifies the relationship between the data mode!, data structures, the design and development of a database and the use of automated tools for systems development. In conclusion, critical success factors for the continuation of the N.G.I.S. developments are identified and the benefits that will accrue are enumerated.

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