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Mathukumalli, Sravya. "Vocal combo android application". Kansas State University, 2016. http://hdl.handle.net/2097/32505.
Pełny tekst źródłaDepartment of Computing and Information Sciences
Mitchell L. Neilsen
Now-a-days people from various backgrounds need different information on demand. People are relying on web as a source of information they need. But to get connected to internet all the time with a computer system is not possible. Android, being open source has already made its mark in the mobile application development. The highest smart phone user base and the ease of developing the applications in Android is an added advantage for the users as well as the Android developers. The vocal combo is an Android application which provides the required functionality on Android supported smart phone or a tablet. This provides the flexibility of accessing information at the users’ fingertips. This application is built using Android SDK, which makes the application easy to deploy on any Android powered device. Vocal Combo is a combination of voice based applications. It includes a Text-To-Voice convertor and Voice-To-Text convertor. This application helps the user to learn the pronunciation of various words. At the same time the user can also check his/her pronunciation skills. This application also provides the functionality of meaning check where the user can check the meaning of the words he types in or speaks out. At any point of time, the user can check the history of the words for which he has checked the meaning or pronunciation for. The application also provides the support to the user on how to use this application.
Benkrid, A. "Real time TLM vocal tract modelling". Thesis, University of Nottingham, 1989. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.352958.
Pełny tekst źródła貴文, 古山, i Takafumi Furuyama. "Vocal recognition in primate : comparison between Japanese macaques and humans". Thesis, https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB13045021/?lang=0, 2017. https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB13045021/?lang=0.
Pełny tekst źródłaWildermoth, Brett Richard, i n/a. "Text-Independent Speaker Recognition Using Source Based Features". Griffith University. School of Microelectronic Engineering, 2001. http://www4.gu.edu.au:8080/adt-root/public/adt-QGU20040831.115646.
Pełny tekst źródłaWildermoth, Brett Richard. "Text-Independent Speaker Recognition Using Source Based Features". Thesis, Griffith University, 2001. http://hdl.handle.net/10072/366289.
Pełny tekst źródłaThesis (Masters)
Master of Philosophy (MPhil)
School of Microelectronic Engineering
Faculty of Engineering and Information Technology
Full Text
Keenan, Sumir. "Identity information in bonobo vocal communication : from sender to receiver". Thesis, Lyon, 2016. http://www.theses.fr/2016LYSES038/document.
Pełny tekst źródłaIdentity information is vital for highly social species as it facilitates individual recognition and allows for differentiation between social partners in many contexts, such as dominance hierarchies, territorial defence, mating and parent-offspringidentification and group cohesion and coordination. In many species vocalisations can be the most effective communication channel through complex environments and over long-distances and are encoded with the stable features of an individual’s voice. Associations between these individual vocal signatures and accumulated social knowledge about conspecifics can greatly increase an animal’s fitness, as it facilitates adaptively constructive social decisions. This thesis investigates the encoding and decoding of identity information in the vocal communication system of the bonobo, Pan paniscus. We firstly investigated the stability of vocal signatures across the five most common call types in the bonobo vocal repertoire. Results showed that while all call types have the potential to code identity information, loud calls used during times of high arousal and for distance communication have the strongest individual vocal signatures. Following the first study, we investigated if social familiarity and relatedness affect the acoustic features that code individual information in the bark call type. Overall, we found strong evidence for vocal convergence, and specifically, that individuals who are related and familiar, independently from one another, are more vocally similar to one another than unrelated and unfamiliar individuals. In a final study we tested if bonobos are capable of using the encoded identity information to recognise past group members that they no longer live with. Through a series playback experiments we demonstrated that bonobos are capable of recognising familiar individuals from vocalisations alone even after years of separation. Collectively, the results of this thesis show that the encoding and decoding of identity information in bonobo vocalisations is a dynamic system, subject to modification through social processes but robust enough to allow for individual recognition over time. In conclusion these studies contribute to a better understanding of the vocal communication system of a non-human primate species with a unique and complex social network
Ma, Zongqiang. "Spontaneous speech recognition using statistical dynamic models for the vocal-tract-resonance dynamics". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0020/NQ53993.pdf.
Pełny tekst źródłaYuditskaya, Sophia. "Automatic vocal recognition of a child's perceived emotional state within the Speechome corpus". Thesis, Massachusetts Institute of Technology, 2010. http://hdl.handle.net/1721.1/62086.
Pełny tekst źródłaCataloged from PDF version of thesis.
Includes bibliographical references (p. 137-149).
With over 230,000 hours of audio/video recordings of a child growing up in the home setting from birth to the age of three, the Human Speechome Project has pioneered a comprehensive, ecologically valid observational dataset that introduces far-reaching new possibilities for the study of child development. By offering In vivo observation of a child's daily life experience at ultra-dense, longitudinal time scales, the Speechome corpus holds great potential for discovering developmental insights that have thus far eluded observation. The work of this thesis aspires to enable the use of the Speechome corpus for empirical study of emotional factors in early child development. To fully harness the benefits of Speechome for this purpose, an automated mechanism must be created to perceive the child's emotional state within this medium. Due to the latent nature of emotion, we sought objective, directly measurable correlates of the child's perceived emotional state within the Speechome corpus, focusing exclusively on acoustic features of the child's vocalizations and surrounding caretaker speech. Using Partial Least Squares regression, we applied these features to build a model that simulates human perceptual heuristics for determining a child's emotional state. We evaluated the perceptual accuracy of models built across child-only, adult-only, and combined feature sets within the overall sampled dataset, as well as controlling for social situations, vocalization behaviors (e.g. crying, laughing, babble), individual caretakers, and developmental age between 9 and 24 months. Child and combined models consistently demonstrated high perceptual accuracy, with overall adjusted R-squared values of 0.54 and 0.58, respectively, and an average of 0.59 and 0.67 per month. Comparative analysis across longitudinal and socio-behavioral contexts yielded several notable developmental and dyadic insights. In the process, we have developed a data mining and analysis methodology for modeling perceived child emotion and quantifying caretaker intersubjectivity that we hope to extend to future datasets across multiple children, as new deployments of the Speechome recording technology are established. Such large-scale comparative studies promise an unprecedented view into the nature of emotional processes in early childhood and potentially enlightening discoveries about autism and other developmental disorders.
by Sophia Yuditskaya.
S.M.
Schall, Sonja. "The face in your voice–how audiovisual learning benefits vocal communication". Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät II, 2014. http://dx.doi.org/10.18452/17039.
Pełny tekst źródłaFace and voice of a person are strongly associated with each other and usually perceived as a single entity. Despite the natural co-occurrence of faces and voices, brain research has traditionally approached their perception from a unisensory perspective. This means that research into face perception has exclusively focused on the visual system, while research into voice perception has exclusively probed the auditory system. In this thesis, I suggest that the brain has adapted to the multisensory nature of faces and voices and that this adaptation is evident even when one input stream is missing, that is, when input is actually unisensory. Specifically, the current work investigates how the brain exploits previously learned voice-face associations to optimize the auditory processing of voices and vocal speech. Three empirical studies providing spatiotemporal brain data—via functional magnetic resonance imaging (fMRI) and magnetoencephalography (MEG)—constitute this thesis. All data were acquired while participants listened to auditory-only speech samples of previously familiarized speakers (with or without seeing the speakers’ faces). Three key findings demonstrate that previously learned visual speaker information support the auditory analysis of vocal sounds: (i) face-sensitive areas were part of the sensory network activated by voices, (ii) the auditory analysis of voices was temporally facilitated by learned facial associations and (iii) multisensory interactions between face- and voice/speech-sensitive regions were increased. The current work challenges traditional unisensory views on vocal perception and rather suggests that voice and vocal speech perception profit from a multisensory neural processing scheme.
Garau, Giulia. "Speaker normalisation for large vocabulary multiparty conversational speech recognition". Thesis, University of Edinburgh, 2009. http://hdl.handle.net/1842/3983.
Pełny tekst źródłaBhullar, Naureen. "Effects of Facial and Vocal Emotion on Word Recognition in 11-to-13-month-old infants". Diss., Virginia Tech, 2007. http://hdl.handle.net/10919/27502.
Pełny tekst źródłaPh. D.
Bonzi, Francesco. "Lyrics Instrumentalness: An Automatic System for Vocal and Instrumental Recognition in Polyphonic Music with Deep Learning". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021.
Znajdź pełny tekst źródłaPanchapagesan, Sankaran. "Frequency warping by linear transformation, and vocal tract inversion for speaker normalization in automatic speech recognition". Diss., Restricted to subscribing institutions, 2008. http://proquest.umi.com/pqdweb?did=1610480121&sid=1&Fmt=2&clientId=1564&RQT=309&VName=PQD.
Pełny tekst źródłaDowell, Sacha. "Mother-pup recognition behaviour, pup vocal signatures and allosuckling in the New Zealand fur seal, Arctocephalus forsteri". Thesis, University of Canterbury. Biological Sciences, 2005. http://hdl.handle.net/10092/1267.
Pełny tekst źródłaRoberts, Briony Z. Jr. "Dialects, Sex-specificity, and Individual Recognition in the Vocal Repertoire of the Puerto Rican Parrot (Amazona vittata)". Thesis, Virginia Tech, 1997. http://hdl.handle.net/10919/79692.
Pełny tekst źródłaMaster of Science
Lima, Alice de Moura. "Production and perception of acoustic signals in captive bottlenose dolphins (Tursiops truncatus) : contextual use of social signals and recognition of artificial labels". Thesis, Rennes 1, 2017. http://www.theses.fr/2017REN1B048/document.
Pełny tekst źródłaStudies on animal bioacoustics, traditionally relying on non-human primate and songbird models, converge towards the idea that social life appears as the main driving force behind the evolution of complex communication. Comparisons with cetaceans is also particularly interesting from an evolutionary point of view. They are indeed mammals forming complex social bonds, with abilities in acoustic plasticity, but that had to adapt to marine life, making habitat another determining selection force. Their natural habitat constrains sound production, usage and perception but, in the same way, constrains ethological observations making studies of captive cetaceans an important source of knowledge on these animals. Beyond the analysis of acoustic structures, the study of the social contexts in which the different vocalizations are used is essential to the understanding of vocal communication. Compared to primates and birds, the social function of dolphins’ acoustic signals remains largely misunderstood. Moreover, the way cetaceans’ vocal apparatus and auditory system adapted morphoanatomically to an underwater life is unique in the animal kingdom. But their ability to perceive sounds produced in the air remains controversial due to the lack of experimental demonstrations. The objectives of this thesis were, on the one hand, to explore the spontaneous contextual usage of acoustic signals in a captive group of bottlenose dolphins and, on the other hand, to test experimentally underwater and aerial abilities in auditory perception. Our first observational study describes the daily life of our dolphins in captivity, and shows that vocal signalling reflects, at a large scale, the temporal distribution of social and non-social activities in a facility under human control. Our second observational study focuses on the immediate context of emission of the three main acoustic categories previously identified in the dolphins’ vocal repertoire, i.e. whistles, burst-pulses and click trains. We found preferential associations between each vocal category and specific types of social interactions and identified context-dependent patterns of sound combinations. Our third study experimentally tested, under standardized conditions, the response of dolphins to human-made individual sound labels broadcast under and above water. We found that dolphins were able to recognize and to react only to their own label, even when broadcast in the air. Apart from confirming aerial hearing, these findings go in line with studies supporting that dolphins possess a concept of identity. Overall, the results obtained during this thesis suggest that some social signals in the dolphin repertoire can be used to communicate specific information about the behavioural contexts of the individuals involved and that individuals are able to generalize their concept of identity for human-generated signals
Keshtiari, Niloofar [Verfasser]. "Does Gender Affect Recognition of Vocal Emotions? : evidence from Persian speakers living in a collectivist society / Niloofar Keshtiari". Berlin : Freie Universität Berlin, 2016. http://d-nb.info/1096221128/34.
Pełny tekst źródłaMadison, Annelise Alissa. "Social Anxiety Symptoms, Heart Rate Variability, and Vocal Emotion Recognition: Evidence of a Normative Vagally-Mediated Positivity Bias in Women". The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu15582676377176.
Pełny tekst źródłaAnglade, Yolande. "Robustesse de la connaissance automatique de la parole : étude et application dans un système d'aide vocal pour une standardiste malvoyante". Nancy 1, 1994. http://www.theses.fr/1994NAN10013.
Pełny tekst źródłaTripovich, Joy Sophie. "Acoustic communication in Australian fur seals". Thesis, The University of Sydney, 2006. http://hdl.handle.net/2123/1690.
Pełny tekst źródłaTripovich, Joy Sophie. "Acoustic communication in Australian fur seals". University of Sydney, 2006. http://hdl.handle.net/2123/1690.
Pełny tekst źródłaCommunication is a fundamental process that allows animals to effectively transfer information between groups or individuals. Recognition plays an essential role in permitting animals to distinguish individuals based upon both communicatory and non-communicatory signals allowing animals to direct suitable behaviours towards them. Several modes of recognition exist and in colonial breeding animals which congregate in large numbers, acoustic signalling is thought to be the most effective as it suffers less from environmental degradation. Otariid seals (fur seals and sea lions) are generally colonial breeding species which congregate at high densities on offshore islands. In contrast to the other Arctocephaline species, the Australian fur seal, Arctocephalus pusillus doriferus, along with its conspecific, the Cape fur seal, A. p. pusillus, display many of the behavioural traits of sea lions. This may have important consequences in terms of its social structure and evolution. The acoustic communication of Australian fur seals was studied on Kanowna Island, Bass Strait, Australia. Analysing the acoustic structure of vocalisations and their use facilitates our understanding of the social function of calls in animal communication. The vocal repertoires of males, females, pups and yearlings were characterised and their behavioural context examined. Call structural variations in males were evident with changes in behavioural context, indicating parallel changes in the emotive state of sender. For a call to be used in vocal recognition it must display stereotypy within callers and variation between them. In Australian fur seal females and pups, individuals were found to have unique calls. Mutual mother-pup recognition has been suggested for otariids and this study supports the potential for this process to occur through the use of vocalisations. Call structural changes in pup vocalisations were also investigated over the progression of the year, from birth to weaning. Vocalisations produced by pups increased in duration, lowered in both the number of parts per call and the harmonic band containing the maximum frequency as they became older, suggesting calls are changing constantly as pups grow toward maturity. It has been suggested through descriptive reports, that the bark call produced by males is important to vocal recognition. The present study quantified this through the analysis of vocalisations produced by male Australian fur seals. Results support descriptive evidence suggesting that male barks can be used to discriminate callers. Traditional playback studies further confirmed that territorial male Australian fur seals respond significantly more to the calls of strangers than to those of neighbours, supporting male vocal recognition. This study modified call features of the bark to determine the importance to vocal recognition. The results indicate that the whole frequency spectrum was important to recognition. There was also an increase in response from males when they heard more bark units, indicating the importance of repetition by a caller. Recognition occurred when males heard between 25-75% of each bark unit, indicating that the whole duration of each bark unit is not necessary for recognition to occur. This may have particular advantages for communication in acoustically complex breeding environments, where parts of calls may be degraded by the environment. The present study examined the life history characteristics of otariids to determine the factors likely to influence and shape its vocal behaviour. Preliminary results indicate that female density, body size and the breeding environment all influence the vocal behaviour of otariids, while duration of lactation and the degree of polygyny do not appear to be influential. Understanding these interactions may help elucidate how vocal recognition and communication have evolved in different pinniped species.
Woods, Richard David. "Collective responses to acoustic threat information in jackdaws". Thesis, University of Exeter, 2016. http://hdl.handle.net/10871/25978.
Pełny tekst źródłaWong, Kim-Yung Eddie. "Automatic spoken language identification utilizing acoustic and phonetic speech information". Thesis, Queensland University of Technology, 2004. https://eprints.qut.edu.au/37259/1/Kim-Yung_Wong_Thesis.pdf.
Pełny tekst źródłaSILVA, Daniella Dias Cavalcante da. "Desenvolvimento de um IP core de pré-processamento digital de sinais de voz para aplicação em sistemas embutidos". Universidade Federal de Campina Grande, 2006. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1293.
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Capes
A fala é o meio de comunicação comumente utilizado pelo homem, que o distingue dos demais seres vivos, permitindo-lhe a troca de idéias, expressão de opiniões ou revelação de seu pensamento. Diante do avanço tecnológico e conseqüente surgimento de equipamentos eletrônicos cada vez mais sofisticados, a possibilidade de permitir a interação homemmáquina através da voz tem sido objeto de grande interesse, tanto do meio acadêmico quanto dos fabricantes de tais equipamentos. Pesquisas na área de Processamento Digital de Sinais de Voz têm permitido o desenvolvimento de sistemas de Resposta Vocal, Reconhecimento de Voz e Reconhecimento de Identidade Vocal. Entretanto, requisitos de processamento ainda dificultam a implementação desses sistemas em dispositivos com baixo poder computacional, como celulares, palmtops e eletrodomésticos. O trabalho desenvolvido consiste do estudo e adaptação de técnicas de processamento digital de sinais de voz, resultando em uma biblioteca de pré-processamento, incluindo as funções de pré-ênfase, divisão em quadros e janelamento, de maneira a permitir sua utilização no desenvolvimento de aplicações embutidas de reconhecimento de voz ou locutor. Foram realizadas adaptações dos modelos necessários à realização das funções, implementação em uma linguagem de descrição de hardware, verificação funcional da biblioteca e, por fim, prototipação em um dispositivo de hardware.
Speech is the most common way of communication used by human beings, which distinguishes it from other living beings, allowing the exchange of ideas, expression of opinions or revelation of thought. In face technology advance and consequently appearance of electronics equipments more and more sophisticated, the possibility to allow the man-machine interaction through speech have been object of interesting as to academic environment as to electronic equipment developers. Research in the area of Speech Processing has been allowing the development of Speech Synthesis Systems, Speech Recognition Systems and Speaker Recognition Systems. However, processing requirements still difficult the implementation of those systems in devices with low computational power, as mobile phone, palmtops and home equipments. This work consists of the study and adaptation of digital processing speech signals techniques, resulting in an optimized library of preprocessing including preemphasis, division into frames and windowing, allowing this use in development of speech or speaker recognition embedded applications. It was made adaptations in the models, implementation in a hardware description language, library functional verification and finally the prototyping in a hardware device.
Regnier, Lise. "Localization, Characterization and Recognition of Singing Voices". Phd thesis, Université Pierre et Marie Curie - Paris VI, 2012. http://tel.archives-ouvertes.fr/tel-00687475.
Pełny tekst źródłaHale, Jennifer Ann. "The Role of Male Vocal Signals During Male-Male Competition and Female Mate Choice in Greater Prairie-Chickens (Tympanuchus cupido)". The Ohio State University, 2013. http://rave.ohiolink.edu/etdc/view?acc_num=osu1365786099.
Pełny tekst źródłaAlsabaan, Majed Soliman K. "Pronunciation support for Arabic learners". Thesis, University of Manchester, 2015. https://www.research.manchester.ac.uk/portal/en/theses/pronunciation-support-for-arabic-learners(3db28816-90ed-4e8b-b64c-4bbd35f98be7).html.
Pełny tekst źródłaEl, Kansouli Mohamed. "Contribution à la commande vocale d'une machine : Application au robot marcheur EMA4". Valenciennes, 1989. https://ged.uphf.fr/nuxeo/site/esupversions/16a27432-2240-4452-8371-17d179e15a53.
Pełny tekst źródłaSklar, Alexander Gabriel. "Channel Modeling Applied to Robust Automatic Speech Recognition". Scholarly Repository, 2007. http://scholarlyrepository.miami.edu/oa_theses/87.
Pełny tekst źródłaZelinka, Petr. "Zvyšování účinnosti strojového rozpoznávání řeči". Doctoral thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2012. http://www.nusl.cz/ntk/nusl-233578.
Pełny tekst źródłaCarvalho, Raphael Torres Santos. "Transformada Wavelet na detecÃÃo de patologias da laringe". Universidade Federal do CearÃ, 2012. http://www.teses.ufc.br/tde_busca/arquivo.php?codArquivo=8908.
Pełny tekst źródłaA quantidade de mÃtodos nÃo invasivos de diagnÃstico tem aumentado devido à necessidade de exames simples, rÃpidos e indolores. Por conta do crescimento da tecnologia que fornece os meios necessÃrios para a extraÃÃo e processamento de sinais, novos mÃtodos de anÃlise tÃm sido desenvolvidos para compreender a complexidade dos sinais de voz. Este trabalho de dissertaÃÃo apresenta uma nova ideia para caracterizar os sinais de voz saudÃvel e patolÃgicos baseado em uma ferramenta matemÃtica amplamente conhecida na literatura, a Transformada Wavelet (WT). O conjunto de dados utilizado neste trabalho consiste de 60 amostras de vozes divididas em quatro classes de amostras, uma de indivÃduos saudÃveis e as outras trÃs de pessoas com nÃdulo vocal, edema de Reinke e disfonia neurolÃgica. Todas as amostras foram gravadas usando a vogal sustentada /a/ do PortuguÃs Brasileiro. Os resultados obtidos por todos os classificadores de padrÃes estudados mostram que a abordagem proposta usando WT à uma tÃcnica adequada para discriminaÃÃo entre vozes saudÃvel e patolÃgica, e apresentaram resultados similares ou superiores a da tÃcnica clÃssica quanto à taxa de reconhecimento.
The amount of non-invasive methods of diagnosis has increased due to the need for simple, quick and painless tests. Due to the growth of technology that provides the means for extraction and signal processing, new analytical methods have been developed to help the understanding of analysis of the complexity of the voice signals. This dissertation presents a new idea to characterize signals of healthy and pathological voice based on one mathematical tools widely known in the literature, Wavelet Transform (WT). The speech data were used in this work consists of 60 voice samples divided into four classes of samples: one from healthy individuals and three from people with vocal fold nodules, Reinkeâs edema and neurological dysphonia. All the samples were recorded using the vowel /a/ in Brazilian Portuguese. The obtained results by all the pattern classifiers studied indicate that the proposed approach using WT is a suitable technique to discriminate between healthy and pathological voices, since they perform similarly to or even better than classical technique, concerning recognition rates.
Favarelli, Elia. "Algoritmi di Machine Learning per il Riconoscimento Vocale". Master's thesis, Alma Mater Studiorum - Università di Bologna, 2017.
Znajdź pełny tekst źródłaKoudache, Abdellah. "Contribution à la reconnaissance vocale en vue de la commande de machine : application au robot marcheur EMA4". Valenciennes, 1993. https://ged.uphf.fr/nuxeo/site/esupversions/121368bf-ebaa-4f19-9a9a-ae9f0c6a7da5.
Pełny tekst źródłaZapata, Rojas Julian. "Traduction dictée interactive : intégrer la reconnaissance vocale à l’enseignement et à la pratique de la traduction professionnelle". Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/23227.
Pełny tekst źródłaLa traduction dictée (TD) est une technique de traduction amplement utilisée avant l’arrivée massive des machines à écrire et des ordinateurs personnels sur les postes de travail des traducteurs professionnels. À l’heure actuelle, devant la demande croissante de traduction à l’ère de la mondialisation et des technologies de l’information et des communications (TIC), certains traducteurs en exercice et des formateurs en traduction du monde entier considèrent la (ré)intégration de la TD à la pratique traductive. Contrairement à la méthode d’il y a quelques décennies, où la transcription des traductions était normalement produite par un copiste professionnel, on considère l’utilisation des technologies de reconnaissance vocale (RV) : des outils informatiques pouvant prendre en charge la transcription de dictées. Bien que les systèmes de RV sur le marché ne soient pas adaptés à la pratique de la traduction spécifiquement, ils semblent apporter, à ceux qui les utilisent déjà, une approche plus ergonomique et plus efficace que la méthode conventionnelle, c’est-à-dire la saisie au clavier d’ordinateur. La présente thèse introduit la notion de traduction dictée interactive (TDI) comme technique de traduction en interaction avec un système de RV. Lors de la revue de la littérature pour le présent projet, nous avons constaté que l’intérêt à intégrer la RV à la traduction professionnelle n’est pas nouveau, mais que les efforts précédents n’ont pas connu de succès définitif. Également, une analyse des besoins de certains traducteurs utilisant des systèmes de RV nous a éclairé sur la nature des motivations de ces traducteurs à se tourner vers la RV, sur leurs opinions vis-à-vis de cette dernière et sur les difficultés que posent les systèmes de RV pour les tâches d’ordre traductif. Notre thèse se veut un premier pas vers la conception d’outils d’aide à la traduction à la fois ergonomiques, c’est-à-dire prenant en compte le facteur humain, et efficaces, permettant de combler les besoins actuels du marché de la traduction. Elle se veut également une proposition de renouvèlement des programmes de formation à la traduction. Intégrer la TDI à la formation et à la pratique traductives, c’est (ré)intégrer des techniques de traduction orale utilisées par le passé et des technologies émergentes de RV. Et pour que cette intégration soit optimale, des défis importants d’ordre technique, cognitif et pédagogique restent à être surmontés.
SILVA, Daniella Dias Cavalcante da. "Reconhecimento de fala contínua para o Português Brasileiro em sistemas embarcados". Universidade Federal de Campina Grande, 2011. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1295.
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Com o advento da tecnologia, as máquinas predominam em quase todos os cenários do cotidiano das pessoas, sejam essas máquinas computadores, eletrodomésticos, dispositivos portáteis, etc. Com isso, nada melhor do que dotá-las com a capacidade de percepção e compreensão da voz humana, que é a forma mais simples, natural e eficaz do ser humano expressar seus pensamentos. Apesar de muitas pesquisas na área de Processamento Digital de Sinais de Voz (PDSV) terem permitido o desenvolvimento de sistemas de Reconhecimento de Faia bastante eficientes, requisitos de processamento ainda dificultam a implementação desses sistemas em dispositivos com pequeno poder computacional, como celulares, palmtops e eíetrodomésticos. Para permitir a implementação de sistemas de Reconhecimento de Faia nesse contexto, alguns trabalhos sacrificam a eficiência no processo de reconhecimento em nome da redução do tamanho físico e de exigências computacionais. Assim, a busca por modelagens acústicas e linguísticas othnizadas, associadas ao uso de bases de dados representativas, pode levar a ura compromisso entre desempenho do sistema em termos de taxas de reconhecimento e exigências computacionais impostas por sistemas embarcados. O objetivo principal deste trabalho consiste na modelagem da arquitetura de um sistema de reconhecimento de fala contínua para o português brasileiro, utilizando Modelos Ocultos de Markov, de forma a possibilitar sua implementação em um sistema embarcado com recursos computacionais limitados. A fim de selecionar a configuração que melhor atenda esse objetivo, foram realizados experimentos e análises, de modo a identificar possíveis adaptações, a partir de simplificações matemáticas e redução de parâmetros nas etapas do processo de reconhecimento. Em todo lho, foi considerada a relação entre a taxa de reconhecimento e o custo computacional. A arquitetura do sistema embarcado desenvolvida e o seu processo de modelagem, incluindo os experimentos, as análises e os seus respectivos resultados, serão apresentados e discutidos no decorrer deste documento.
WIth the advent of technology, machines predominate in aímost ali seenarios of everyday life. The possibiiity of performing human-maehine comniunication through speech makes this interact.ion easier and more productive. However, processing requirements still difficult tlíe implementation oF systems for automatic continuous speech recognition on devices with low computational power sucJi as mobile phones, palmtops and appliances. To allow the implementation of speech recognition systems in this context. some works sacrifice efficiency in the recognition process for redueing the chip area and computational requirements. For this purpose, it becomes necessary to research for optimized acoustic and language modeling, associated with use of representative databases, looking for a good compromise between recognitioa vaies and compuiational demands imposed by embedded systems. The main goai of this work is to model the architecture of a system for continuous speech recognition Brazilian Portuguese, in order to enable its implementation in an embedded system with limited computtng resources. In order to select the setting that best nieets this goal, experiments and analysis were performed. The purpose of these was to identify possible adaptations, from mathematical simpiifícations and reduction of parameters in the steps of the recognition process. During the deveiopinent of this work, the relationship between recognition rate and computational cost was considered. The embedded system architecture developed and its modeling process, including experiments. analysis and their results will be presented and díscussed thxoughout this document.
Boué, Anaïs. "Data mining and volcanic eruption forcasting". Thesis, Université Grenoble Alpes (ComUE), 2015. http://www.theses.fr/2015GREAU007/document.
Pełny tekst źródłaEruption forecasting methods are valuable tools for supporting decision making during volcanic crises if they are integrated in a global monitoring strategy and if their potentiality and limitations are known. Many attempts for deterministic forecasting of volcanic eruptions and landslides have been performed using the material Failure Forecast Method (FFM). This method consists in adjusting an empirical power law on precursory patterns of seismicity or deformation. Until now, most of the studies have presented hindsight forecasts, based on complete time series of precursors, and do not evaluate the method's potential for carrying out real-time forecasting with partial precursory sequences. Moreover, the limited number of published examples and the absence of systematic application of the FFM makes it difficult to conclude as to the ability of the method to forecast volcanic eruptions. Thus it appears important to gain experience by carrying out systematic forecasting attempts in various eruptive contexts. In this thesis, I present a rigorous approach of the FFM designed for real-time applications on volcano-seismic precursors. I use a Bayesian approach based on the FFM theory and an automatic classification of the seismic events that do not have the same source mechanisms. The probability distributions of the data deduced from the performance of the classification are used as input. As output, the method provides the probability of the forecast time at each observation time before the eruption. The spread of the posterior probability density function of the prediction time and its stability with respect to the observation time are used as criteria to evaluate the reliability of the forecast. I show that the method developed here outperforms the classical application of the FFM both for hindsight and real-time attempts because it accurately takes the uncertainty of the data information into account. The automatic classification of volcano-seismic signals allows for a systematic application of this forecasting method to decades of seismic data from andesitic volcanoes including Volcan de Colima (Mexico) and Merapi volcano (Indonesia), and from the basaltic volcano of Piton de la Fournaise (Reunion Island, France). The number of eruptions that are not preceded by precursors is quantified, as well as the number of seismic crises that are not followed by eruptions. Then, I use 64 precursory sequences and apply the forecasting method developed in this thesis. I thus determine in which conditions the FFM can be successfully applied and I quantify the success rate of the method in real-time and in hindsight. Only 62% of the precursory sequences analysed in this thesis were suitable for the application of FFM and half of the total number of eruptions are successfully forecast in hindsight. In real-time, the method allows for the successful predictions of only 36% of the total of all eruptions considered. Nevertheless, real-time predictions are successful for 83% of the cases that fulfil the reliability criteria. Therefore, we can have a good confidence on the method when the reliability criteria are met, but the deterministic real-time forecasting tool developed in this thesis is not sufficient in itself. However, it could potentially be informative combined with other forecasting methods and supervised by an observer. These results reflect the lack of knowledge concerning the pre-eruptive mechanisms
Srinivasamurthy, Ajay. "A Data-driven bayesian approach to automatic rhythm analysis of indian art music". Doctoral thesis, Universitat Pompeu Fabra, 2016. http://hdl.handle.net/10803/398986.
Pełny tekst źródłaLarge and growing collections of a wide variety of music are now available on demand to music listeners, necessitating novel ways of automatically structuring these collections using different dimensions of music. Rhythm is one of the basic music dimensions and its automatic analysis, which aims to extract musically meaningful rhythm related information from music, is a core task in Music Information Research (MIR). Musical rhythm, similar to most musical dimensions, is culture-specific and hence its analysis requires culture-aware approaches. Indian art music is one of the major music traditions of the world and has complexities in rhythm that have not been addressed by the current state of the art in MIR, motivating us to choose it as the primary music tradition for study. Our intent is to address unexplored rhythm analysis problems in Indian art music to push the boundaries of the current MIR approaches by making them culture-aware and generalizable to other music traditions. The thesis aims to build data-driven signal processing and machine learning approaches for automatic analysis, description and discovery of rhythmic structures and patterns in audio music collections of Indian art music. After identifying challenges and opportunities, we present several relevant research tasks that open up the field of automatic rhythm analysis of Indian art music. Data-driven approaches require well curated data corpora for research and efforts towards creating such corpora and datasets are documented in detail. We then focus on the topics of meter analysis and percussion pattern discovery in Indian art music. Meter analysis aims to align several hierarchical metrical events with an audio recording. Meter analysis tasks such as meter inference, meter tracking and informed meter tracking are formulated for Indian art music. Different Bayesian models that can explicitly incorporate higher level metrical structure information are evaluated for the tasks and novel extensions are proposed. The proposed methods overcome the limitations of existing approaches and their performance indicate the effectiveness of informed meter analysis. Percussion in Indian art music uses onomatopoeic oral mnemonic syllables for the transmission of repertoire and technique, providing a language for percussion. We use these percussion syllables to define, represent and discover percussion patterns in audio recordings of percussion solos. We approach the problem of percussion pattern discovery using hidden Markov model based automatic transcription followed by an approximate string search using a data derived percussion pattern library. Preliminary experiments on Beijing opera percussion patterns, and on both tabla and mridangam solo recordings in Indian art music demonstrate the utility of percussion syllables, identifying further challenges to building practical discovery systems. The technologies resulting from the research in the thesis are a part of the complete set of tools being developed within the CompMusic project for a better understanding and organization of Indian art music, aimed at providing an enriched experience with listening and discovery of music. The data and tools should also be relevant for data-driven musicological studies and other MIR tasks that can benefit from automatic rhythm analysis.
Les col·leccions de música són cada vegada més grans i variades, fet que fa necessari buscar noves fórmules per a organitzar automàticament aquestes col·leccions. El ritme és una de les dimensions bàsiques de la música, i el seu anàlisi automàtic és una de les principals àrees d'investigació en la disciplina de l'recuperació de la informació musical (MIR, acrònim de la traducció a l'anglès). El ritme, com la majoria de les dimensions musicals, és específic per a cada cultura i per tant, el seu anàlisi requereix de mètodes que incloguin el context cultural. La complexitat rítmica de la música clàssica de l'Índia, una de les tradicions musicals més grans al món, no ha estat encara treballada en el camp d'investigació de MIR - motiu pel qual l'escollim com a principal material d'estudi. La nostra intenció és abordar les problemàtiques que presenta l'anàlisi rítmic de la música clàssica de l'Índia, encara no tractades en MIR, amb la finalitat de contribuir en la disciplina amb nous models sensibles al context cultural i generalitzables a altres tradicions musicals. L'objectiu de la tesi consisteix en desenvolupar tècniques de processament de senyal i d'aprenentatge automàtic per a l'anàlisi, descripció i descobriment automàtic d'estructures i patrons rítmics en col·leccions de música clàssica de l'Índia. Després d'identificar els reptes i les oportunitats, així com les diverses tasques d'investigació rellevants per a aquest objectiu, detallem el procés d'elaboració del corpus de dades, fonamentals per als mètodes basats en dades. A continuació, ens centrem en les tasques d'anàlisis mètric i descobriment de patrons de percussió. L'anàlisi mètric consisteix en alinear els diversos esdeveniments mètrics -a diferents nivells- que es produeixen en una gravació d'àudio. En aquesta tesi formulem les tasques de deducció, seguiment i seguiment informat de la mètrica. D'acord amb la tradició musical estudiada, s'avaluen diferents models bayesians que poden incorporar explícitament estructures mètriques d'alt nivell i es proposen noves extensions per al mètode. Els mètodes proposats superen les limitacions dels mètodes ja existents i el seu rendiment indica l'efectivitat dels mètodes informats d'anàlisis mètric. La percussió en la música clàssica de l'Índia utilitza onomatopeies per a la transmissió del repertori i de la tècnica, fet que construeix un llenguatge per a la percussió. Utilitzem aquestes síl·labes percussives per a definir, representar i descobrir patrons en enregistraments de solos de percussió. Enfoquem el problema del descobriment de patrons percussius amb un model de transcripció automàtica basat en models ocults de Markov, seguida d'una recerca aproximada de strings utilitzant una llibreria de patrons de percussions derivada de dades. Experiments preliminars amb patrons de percussió d'òpera de Pequín, i amb gravacions de solos de tabla i mridangam, demostren la utilitat de les síl·labes percussives. Identificant, així, nous horitzons per al desenvolupament de sistemes pràctics de descobriment. Les tecnologies resultants d'aquesta recerca són part de les eines desenvolupades dins el projecte de CompMusic, que té com a objectiu millorar l'experiència d'escoltar i descobrir música per a la millor comprensió i organització de la música clàssica de l'Índia, entre d'altres. Aquestes dades i eines poden ser rellevants per a estudis musicològics basats en dades i, també, altres tasques MIR poden beneficiar-se de l'anàlisi automàtic del ritme.
Patino, Villar José María. "Efficient speaker diarization and low-latency speaker spotting". Thesis, Sorbonne université, 2019. http://www.theses.fr/2019SORUS003/document.
Pełny tekst źródłaSpeaker diarization (SD) involves the detection of speakers within an audio stream and the intervals during which each speaker is active, i.e. the determination of ‘who spoken when’. The first part of the work presented in this thesis exploits an approach to speaker modelling involving binary keys (BKs) as a solution to SD. BK modelling is efficient and operates without external training data, as it operates using test data alone. The presented contributions include the extraction of BKs based on multi-resolution spectral analysis, the explicit detection of speaker changes using BKs, as well as SD fusion techniques that combine the benefits of both BK and deep learning based solutions. The SD task is closely linked to that of speaker recognition or detection, which involves the comparison of two speech segments and the determination of whether or not they were uttered by the same speaker. Even if many practical applications require their combination, the two tasks are traditionally tackled independently from each other. The second part of this thesis considers an application where SD and speaker recognition solutions are brought together. The new task, coined low latency speaker spotting (LLSS), involves the rapid detection of known speakers within multi-speaker audio streams. It involves the re-thinking of online diarization and the manner by which diarization and detection sub-systems should best be combined
Liu, Jia-Ge, i 劉佳格. "Vocal password recognition". Thesis, 2014. http://ndltd.ncl.edu.tw/handle/25956858531137285592.
Pełny tekst źródła國立臺灣大學
工程科學及海洋工程學研究所
102
The purpose of this study is to identify speaker by vocal password recognition. Each password includes four Chinese characters. Once a examinee speaks a password, energy method was used to separate the characters in the password. The characteristic frequencies of each character were obtained by calculating its first, second and third moments of the amplitude spectrum. The characteristic frequencies were used to recognize speaker’s identities. The sampled data included data for training and testing. The training data set was used to obtain the threshold and scoring rule in recognition process. The testing data set was used to verify the accuracy of the recognition method. Three different Chinese phases were investigated. The identification rates for each phase were 90%, 88% and 90%. It is inferred that the proposed method for vocal password recognition is very feasible.
"Speaker recognition using complementary information from vocal source and vocal tract". Thesis, 2005. http://library.cuhk.edu.hk/record=b6074159.
Pełny tekst źródłaFor speaker verification, a text-dependent weighting scheme is developed. Analysis results show that the source-tract discrimination ratio varies significantly across different sounds due to the diversity of vocal system configurations in speech production. This thesis analyzes the source-tract speaker discrimination ratio for the 10 Cantonese digits, upon which a digit-dependent source-tract weighting scheme is developed. Information fusion with such digit-dependent weights relatively improves the verification performance by 39.6% in matched conditions.
This thesis investigates the feasibility of using both vocal source and vocal tract information to improve speaker recognition performance. Conventional speaker recognition systems typically employ vocal tract related acoustic features, e.g the Mel-frequency cepstral coefficients (MFCC), for discriminative purpose. Motivated by the physiological significance of the vocal source and vocal tract system in speech production, this thesis develops a speaker recognition system to effectively incorporate these two complementary information sources for improved performance and robustness.
This thesis presents a novel approach of representing the speaker-specific vocal source characteristics. The linear predictive (LP) residual signal is adopted as a good representative of the vocal source excitation, in which the speaker specific information resides on both time and frequency domains. Haar transform and wavelet transform are applied for multi-resolution analyses of the LP residual signal. The resulting vocal source features, namely the Haar octave coefficients of residues (HOCOR) and wavelet octave coefficients of residues (WOCOR), can effectively extract the speaker-specific spectro-temporal characteristics of the LP residual signal. Particularly, with pitch-synchronous wavelet transform, the WOCOR feature set is capable of capturing the pitch-related low frequency properties and the high frequency information associated with pitch epochs, as well as their temporal variations within a pitch period and over consecutive periods. The generated vocal source and vocal tract features are complementary to each other since they are derived from two orthogonal components, the LP residual signal and LP coefficients. Therefore they can be fused to provide better speaker recognition performance. A preliminary scheme of fusing MFCC and WOCOR together illustrated that the identification and verification performance can be respectively improved by 34.6% and 23.6%, both in matched conditions.
To maximize the benefit obtained through the fusion of source and tract information, speaker discrimination dependent fusion techniques have been developed. For speaker identification, a confidence measure, which indicates the reliability of vocal source feature in speaker identification, is derived based on the discrimination ratio between the source and tract features in each identification trial. Information fusion with confidence measure offers better weighted scores given by the two features and avoids possible errors introduced by incorporating source information, thereby improves the identification performance further. Compared with MFCC, relative improvement of 46.8% has been achieved.
Zheng Nengheng.
"November 2005."
Adviser: Pak-Chung Ching.
Source: Dissertation Abstracts International, Volume: 67-11, Section: B, page: 6647.
Thesis (Ph.D.)--Chinese University of Hong Kong, 2005.
Includes bibliographical references (p. 123-135).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [200-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstracts in English and Chinese.
School code: 1307.
Wu, Yi-Chung, i 吳逸中. "Recognition of Vocal and Non-Vocal Segments in Musical Sound Tracks". Thesis, 2012. http://ndltd.ncl.edu.tw/handle/2dkh4f.
Pełny tekst źródła國立臺北科技大學
資訊工程系研究所
100
In this thesis, we use MFCC, LPC, LPCC feature extractions and HMM(Hidden Markov Model) tool to do training and create a model. Then use the model to recognize the testing songs. The songs in the database will be separated into two parts, training songs and testing songs. We compare MFCC and LPCC Likelihood difference to increase the recognition rate.In addition, we tried to recognize the Vocal and Non-Vocal segments by computing correlation coefficient of left channel and right channel of the stereo songs.
LUO, GUANG-CUN, i 羅廣村. "Intelligent Recognition System for Vocal Folds Disorder". Thesis, 2009. http://ndltd.ncl.edu.tw/handle/10599482937880025712.
Pełny tekst źródła國立臺灣科技大學
高分子系
97
The purpose of this study was to develop an intelligent recognition system for vocal cord disorders. The image processing technology and neural networks were applied to identify different disease conditions of vocal cords, including the presence of paralysis, tumor, malignant cancer, or no diseases. We first changed three random sets of original obtained images into a grayscale format, followed by applying histogram equalization to obtain a good contrast. We then used statistical threshold to segment the processed images. The binary images were lastly computed by labeling, dilation and erosion to obtain the position of the glottis. The features of the three sets of images would be the input of the neural network. After testing 95 samples, the experimental results reveal that the third set had the best recognition rate reaching 93.6%. The results of this experiment support that the intelligent recognition system has the ability to identify vocal cord disorder. Thereby the problems obtained from misdiagnosis and subjective knowledge in the medical field could be reduced effectively.
"Robust speaker recognition using both vocal source and vocal tract features estimated from noisy input utterances". 2007. http://library.cuhk.edu.hk/record=b5893317.
Pełny tekst źródłaThesis (M.Phil.)--Chinese University of Hong Kong, 2007.
Includes bibliographical references (leaves 106-115).
Abstracts in English and Chinese.
Chapter 1 --- Introduction --- p.1
Chapter 1.1 --- Introduction to Speech and Speaker Recognition --- p.1
Chapter 1.2 --- Difficulties and Challenges of Speaker Authentication --- p.6
Chapter 1.3 --- Objectives and Thesis Outline --- p.7
Chapter 2 --- Speaker Recognition System --- p.10
Chapter 2.1 --- Baseline Speaker Recognition System Overview --- p.10
Chapter 2.1.1 --- Feature Extraction --- p.12
Chapter 2.1.2 --- Pattern Generation and Classification --- p.24
Chapter 2.2 --- Performance Evaluation Metric for Different Speaker Recognition Tasks --- p.30
Chapter 2.3 --- Robustness of Speaker Recognition System --- p.30
Chapter 2.3.1 --- Speech Corpus: CU2C --- p.30
Chapter 2.3.2 --- Noise Database: NOISEX-92 --- p.34
Chapter 2.3.3 --- Mismatched Training and Testing Conditions --- p.35
Chapter 2.4 --- Summary --- p.37
Chapter 3 --- Speaker Recognition System using both Vocal Tract and Vocal Source Features --- p.38
Chapter 3.1 --- Speech Production Mechanism --- p.39
Chapter 3.1.1 --- Speech Production: An Overview --- p.39
Chapter 3.1.2 --- Acoustic Properties of Human Speech --- p.40
Chapter 3.2 --- Source-filter Model and Linear Predictive Analysis --- p.44
Chapter 3.2.1 --- Source-filter Speech Model --- p.44
Chapter 3.2.2 --- Linear Predictive Analysis for Speech Signal --- p.46
Chapter 3.3 --- Vocal Tract Features --- p.51
Chapter 3.4 --- Vocal Source Features --- p.52
Chapter 3.4.1 --- Source Related Features: An Overview --- p.52
Chapter 3.4.2 --- Source Related Features: Technical Viewpoints --- p.54
Chapter 3.5 --- Effects of Noises on Speech Properties --- p.55
Chapter 3.6 --- Summary --- p.61
Chapter 4 --- Estimation of Robust Acoustic Features for Speaker Discrimination --- p.62
Chapter 4.1 --- Robust Speech Techniques --- p.63
Chapter 4.1.1 --- Noise Resilience --- p.64
Chapter 4.1.2 --- Speech Enhancement --- p.64
Chapter 4.2 --- Spectral Subtractive-Type Preprocessing --- p.65
Chapter 4.2.1 --- Noise Estimation --- p.66
Chapter 4.2.2 --- Spectral Subtraction Algorithm --- p.66
Chapter 4.3 --- LP Analysis of Noisy Speech --- p.67
Chapter 4.3.1 --- LP Inverse Filtering: Whitening Process --- p.68
Chapter 4.3.2 --- Magnitude Response of All-pole Filter in Noisy Condition --- p.70
Chapter 4.3.3 --- Noise Spectral Reshaping --- p.72
Chapter 4.4 --- Distinctive Vocal Tract and Vocal Source Feature Extraction . . --- p.73
Chapter 4.4.1 --- Vocal Tract Feature Extraction --- p.73
Chapter 4.4.2 --- Source Feature Generation Procedure --- p.75
Chapter 4.4.3 --- Subband-specific Parameterization Method --- p.79
Chapter 4.5 --- Summary --- p.87
Chapter 5 --- Speaker Recognition Tasks & Performance Evaluation --- p.88
Chapter 5.1 --- Speaker Recognition Experimental Setup --- p.89
Chapter 5.1.1 --- Task Description --- p.89
Chapter 5.1.2 --- Baseline Experiments --- p.90
Chapter 5.1.3 --- Identification and Verification Results --- p.91
Chapter 5.2 --- Speaker Recognition using Source-tract Features --- p.92
Chapter 5.2.1 --- Source Feature Selection --- p.92
Chapter 5.2.2 --- Source-tract Feature Fusion --- p.94
Chapter 5.2.3 --- Identification and Verification Results --- p.95
Chapter 5.3 --- Performance Analysis --- p.98
Chapter 6 --- Conclusion --- p.102
Chapter 6.1 --- Discussion and Conclusion --- p.102
Chapter 6.2 --- Suggestion of Future Work --- p.104
Zhang, Yu Long, i 張裕隆. "The analysis and recognition of human vocal emotions". Thesis, 1994. http://ndltd.ncl.edu.tw/handle/61261274473123342766.
Pełny tekst źródłaMai, Chun-Cheng, i 麥鈞程. "Convolutional Neural Networks for Vocal Password Recognition System". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/7r958r.
Pełny tekst źródła國立臺灣大學
工程科學及海洋工程學研究所
107
There are many different types of biometric systems that are developed because of the need for security and convenience. The biometric technology is based on the unique biological characteristics of each organism such as fingerprint recognition, iris recognition, etc. The voice recognition is also one of the biometric characteristic. One day, people may unlock their cellphone by just talking to their cellphone which make life more convenient. Deep Learning has become one of the most popular research topic becase of ALPHAGO. Everyone started to study how to apply deep learning to a variety of problems and the convolutional neural networks is also an important area in the development of neural networks. This research proposes a vocal password recognition system based on convolutional neural network. Using the grayscale image generated by the speaker’s voice signals as an input to the convolutional neural network and use it to produce the classfication result to build the vocal password recognition system.
"Use of vocal source features in speaker segmentation". 2006. http://library.cuhk.edu.hk/record=b5892857.
Pełny tekst źródłaThesis (M.Phil.)--Chinese University of Hong Kong, 2006.
Includes bibliographical references (leaves 77-82).
Abstracts in English and Chinese.
Chapter Chapter1 --- Introduction --- p.1
Chapter 1.1 --- Speaker recognition --- p.1
Chapter 1.2 --- State of the art of speaker recognition techniques --- p.2
Chapter 1.3 --- Motivations --- p.5
Chapter 1.4 --- Thesis outline --- p.6
Chapter Chapter2 --- Acoustic Features --- p.8
Chapter 2.1 --- Speech production --- p.8
Chapter 2.1.1 --- Physiology of speech production --- p.8
Chapter 2.1.2 --- Source-filter model --- p.11
Chapter 2.2 --- Vocal tract and vocal source related acoustic features --- p.14
Chapter 2.3 --- Linear predictive analysis of speech --- p.15
Chapter 2.4 --- Features for speaker recognition --- p.16
Chapter 2.4.1 --- Vocal tract related features --- p.17
Chapter 2.4.2 --- Vocal source related features --- p.19
Chapter 2.5 --- Wavelet octave coefficients of residues (WOCOR) --- p.20
Chapter Chapter3 --- Statistical approaches to speaker recognition --- p.24
Chapter 3.1 --- Statistical modeling --- p.24
Chapter 3.1.1 --- Classification and modeling --- p.24
Chapter 3.1.2 --- Parametric vs non-parametric --- p.25
Chapter 3.1.3 --- Gaussian mixture model (GMM) --- p.25
Chapter 3.1.4 --- Model estimation --- p.27
Chapter 3.2 --- Classification --- p.28
Chapter 3.2.1 --- Multi-class classification for speaker identification --- p.28
Chapter 3.2.2 --- Two-speaker recognition --- p.29
Chapter 3.2.3 --- Model selection by statistical model --- p.30
Chapter 3.2.4 --- Performance evaluation metric --- p.31
Chapter Chapter4 --- Content dependency study of WOCOR and MFCC --- p.32
Chapter 4.1 --- Database: CU2C --- p.32
Chapter 4.2 --- Methods and procedures --- p.33
Chapter 4.3 --- Experimental results --- p.35
Chapter 4.4 --- Discussion --- p.36
Chapter 4.5 --- Detailed analysis --- p.39
Summary --- p.41
Chapter Chapter5 --- Speaker Segmentation --- p.43
Chapter 5.1 --- Feature extraction --- p.43
Chapter 5.2 --- Statistical methods for segmentation and clustering --- p.44
Chapter 5.2.1 --- Segmentation by spectral difference --- p.44
Chapter 5.2.2 --- Segmentation by Bayesian information criterion (BIC) --- p.47
Chapter 5.2.3 --- Segment clustering by BIC --- p.49
Chapter 5.3 --- Baseline system --- p.50
Chapter 5.3.1 --- Algorithm --- p.50
Chapter 5.3.2 --- Speech database --- p.52
Chapter 5.3.3 --- Performance metric --- p.53
Chapter 5.3.4 --- Results --- p.58
Summary --- p.60
Chapter Chapter6 --- Application of vocal source features in speaker segmentation --- p.61
Chapter 6.1 --- Discrimination power of WOCOR against MFCC --- p.61
Chapter 6.1.1 --- Experimental set-up --- p.62
Chapter 6.1.2 --- Results --- p.63
Chapter 6.2 --- Speaker segmentation using vocal source features --- p.67
Chapter 6.2.1 --- The construction of new proposed system --- p.67
Summary --- p.72
Chapter Chapter7 --- Conclusions --- p.74
Reference --- p.77
De, Armas Winston. "Vocal Frequency Estimation and Voicing State Prediction with Surface EMG Pattern Recognition". Thesis, 2013. http://hdl.handle.net/1807/35596.
Pełny tekst źródłaLove, Christopher D. "A speech recognition system using a neural network model for vocal shaping". 1991. http://hdl.handle.net/1993/18261.
Pełny tekst źródła"Exploitation of phase and vocal excitation modulation features for robust speaker recognition". Thesis, 2011. http://library.cuhk.edu.hk/record=b6075192.
Pełny tekst źródłaSpeaker recognition (SR) refers to the process of automatically determining or verifying the identity of a person based on his or her voice characteristics. In practical applications, a voice can be used as one of the modalities in a multimodal biometric system, or be the sole medium for identity authentication. The general area of speaker recognition encompasses two fundamental tasks: speaker identification and speaker verification.
Wang, Ning.
Adviser: Pak-Chung Ching.
Source: Dissertation Abstracts International, Volume: 73-06, Section: B, page: .
Thesis (Ph.D.)--Chinese University of Hong Kong, 2011.
Includes bibliographical references (leaves 177-193).
Electronic reproduction. Hong Kong : Chinese University of Hong Kong, [2012] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Electronic reproduction. [Ann Arbor, MI] : ProQuest Information and Learning, [201-] System requirements: Adobe Acrobat Reader. Available via World Wide Web.
Abstract also in Chinese.
Wan, Hung-Wei, i 萬鴻緯. "Deep Neural Network-based Anomaly Detection and Recognition in Endoscopic Images of Vocal Folds". Thesis, 2019. http://ndltd.ncl.edu.tw/handle/mtmv4t.
Pełny tekst źródła元智大學
電機工程學系甲組
107
With the great success of deep learning in computer vision in recent years, it has gradually been applied to many fields, and the paper mainly combines it with biomedicine. Using deep learning on images, the vocal fold medical images captured by the endoscopes are analyzed to automatically detect the location of the vocal fold disorders and distinguish the classes. This technique will be able to assist doctors in the diagnosis of the disease. Different from the previous analysis of vocal fold medical images that needs manual process of the selection of proper images for input. Instead, we analyze each frame of the whole video automatically, and only retain the key frames for subsequent calculation. Doing so will not only reduce labor-intensive operations but also be practical for clinical applications. We propose a system with two stages. Stage 1 is responsible for extracting the ROI from each frame in the vocal fold endoscopy films and stage 2 mainly detects the location of the vocal fold disorders from the extracted ROI by our developed deep learning model. Experiments have shown that our system achieves 79% sensitivity and 96% specificity in recognition of healthy and unhealthy cases, and achieves an accuracy rate of approximately 80% in classification of 3-class disorders.