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Dissertations / Theses on the topic 'Signal processing; Voice recognition'

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1

Nayfeh, Taysir H. "Multi-signal processing for voice recognition in noisy environments." Thesis, This resource online, 1991. http://scholar.lib.vt.edu/theses/available/etd-10222009-125021/.

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2

Fredrickson, Steven Eric. "Neural networks for speaker identification." Thesis, University of Oxford, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294364.

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3

Little, M. A. "Biomechanically informed nonlinear speech signal processing." Thesis, University of Oxford, 2007. http://ora.ox.ac.uk/objects/uuid:6f5b84fb-ab0b-42e1-9ac2-5f6acc9c5b80.

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Linear digital signal processing based around linear, time-invariant systems theory finds substantial application in speech processing. The linear acoustic source-filter theory of speech production provides ready biomechanical justification for using linear techniques. Nonetheless, biomechanical studies surveyed in this thesis display significant nonlinearity and non-Gaussinity, casting doubt on the linear model of speech production. In order therefore to test the appropriateness of linear systems assumptions for speech production, surrogate data techniques can be used. This study uncovers sys
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4

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.

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This dissertation is concerned with the problem of describing the singing voice within the audio signal of a song. This work is motivated by the fact that the lead vocal is the element that attracts the attention of most listeners. For this reason it is common for music listeners to organize and browse music collections using information related to the singing voice such as the singer name. Our research concentrates on the three major problems of music information retrieval: the localization of the source to be described (i.e. the recognition of the elements corresponding to the singing voice
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5

Adami, Andre Gustavo. "Sistema de reconhecimento de locutor utilizando redes neurais artificiais." reponame:Biblioteca Digital de Teses e Dissertações da UFRGS, 1997. http://hdl.handle.net/10183/18277.

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Este trabalho envolve o emprego de recentes tecnologias ligadas a promissora área de Inteligência Computacional e a tradicional área de Processamento de Sinais Digitais. Tem por objetivo o desenvolvimento de uma aplicação especifica na área de Processamento de Voz: o reconhecimento de locutor. Inúmeras aplicações, ligadas principalmente a segurança e controle, são possíveis a partir do domínio da tecnologia de reconhecimento de locutor, tanto no que diz respeito a identificação quanto a verificação de diferentes locutores. O processo de reconhecimento de locutor pode ser dividido em duas grand
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6

Stolfi, Rumiko Oishi. "Sintese e reconhecimento da fala humana." [s.n.], 2006. http://repositorio.unicamp.br/jspui/handle/REPOSIP/276267.

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Orientadores: Fabio Violaro, Anamaria Gomide<br>Dissertação (mestrado profissional) - Universidade Estadual de Campinas, Instituto de Computação<br>Made available in DSpace on 2018-08-07T21:57:26Z (GMT). No. of bitstreams: 1 Stolfi_RumikoOishi_M.pdf: 1514197 bytes, checksum: e93f45916d359641c73b31b00952a914 (MD5) Previous issue date: 2006<br>Resumo: O objetivo deste trabalho é apresentar uma revisão dos principais conceitos e métodos envolvidos na síntese, processamento e reconhecimento da fala humana por computador.Estas tecnologias têm inúmeras aplicações, que têm aumentado substancialment
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7

Clotworthy, Christopher John. "A study of automated voice recognition." Thesis, Queen's University Belfast, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.356909.

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8

Wells, Ian. "Digital signal processing architectures for speech recognition." Thesis, University of the West of England, Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294705.

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9

Aggoun, Amar. "DPCM video signal/image processing." Thesis, University of Nottingham, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.335792.

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10

Morris, Robert W. "Enhancement and recognition of whispered speech." Diss., Available online, Georgia Institute of Technology, 2004:, 2003. http://etd.gatech.edu/theses/available/etd-04082004-180338/unrestricted/morris%5frobert%5fw%5f200312%5fphd.pdf.

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11

Rex, James Alexander. "Microphone signal processing for speech recognition in cars." Thesis, University of Southampton, 2000. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.326728.

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12

Shah, Afnan Arafat. "Improving automatic speech recognition transcription through signal processing." Thesis, University of Southampton, 2017. https://eprints.soton.ac.uk/418970/.

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Automatic speech recognition (ASR) in the educational environment could be a solution to address the problem of gaining access to the spoken words of a lecture for many students who find lectures hard to understand, such as those whose mother tongue is not English or who have a hearing impairment. In such an environment, it is difficult for ASR to provide transcripts with Word Error Rates (WER) less than 25% for the wide range of speakers. Reducing the WER reduces the time and therefore cost of correcting errors in the transcripts. To deal with the variation of acoustic features between speake
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13

Doukas, Nikolaos. "Voice activity detection using energy based measures and source separation." Thesis, Imperial College London, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.245220.

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14

Oddiraju, Swetha. "Improving performance for adaptive filtering with voice applications." Diss., Columbia, Mo. : University of Missouri-Columbia, 2007. http://hdl.handle.net/10355/6271.

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Thesis (M.S.)--University of Missouri-Columbia, 2007.<br>The entire dissertation/thesis text is included in the research.pdf file; the official abstract appears in the short.pdf file (which also appears in the research.pdf); a non-technical general description, or public abstract, appears in the public.pdf file. Title from title screen of research.pdf file (viewed on September 29, 2008) Includes bibliographical references.
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15

Hanna, Salim Alia. "Digital signal processing algorithms for speech coding and recognition." Thesis, Imperial College London, 1987. http://hdl.handle.net/10044/1/46268.

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16

YOUSSIF, ROSHDY S. "HYBRID INTELLIGENT SYSTEMS FOR PATTERN RECOGNITION AND SIGNAL PROCESSING." University of Cincinnati / OhioLINK, 2004. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1085714219.

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17

Nosa, Ogbewi. "Signal Processing and patternrecognition algorithm for monitoringParkinson’s disease." Thesis, Högskolan Dalarna, Datateknik, 2006. http://urn.kb.se/resolve?urn=urn:nbn:se:du-2376.

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This masters thesis describes the development of signal processing and patternrecognition in monitoring Parkison’s disease. It involves the development of a signalprocess algorithm and passing it into a pattern recogniton algorithm also. Thesealgorithms are used to determine , predict and make a conclusion on the study ofparkison’s disease. We get to understand the nature of how the parkinson’s disease isin humans.
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18

Wilson, Shawn C. "Voice recognition systems : assessment of implementation aboard U.S. naval ships." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2003. http://library.nps.navy.mil/uhtbin/hyperion-image/03Mar%5FWilson.pdf.

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Thesis (M.S. in Information Systems and Operations)--Naval Postgraduate School, March 2003.<br>Thesis advisor(s): Michael T. McMaster, Kenneth J. Hagan. Includes bibliographical references (p. 47-49). Also available online.
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19

Wu, Ping. "Kohonen self-organising neural networks in speech signal processing." Thesis, University of Reading, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386985.

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20

Johnson, Joanna. "The effectiveness of voice recognition technology as used by persons with disabilities." Online version, 1998. http://www.uwstout.edu/lib/thesis/1998/1998johnsonj.pdf.

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21

Watkins, L. R. "Optical fibre communications : signal processing to accommodate system impairments." Thesis, Bangor University, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.279143.

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22

Smith, Philip F. "Surface evaluation by the signal processing of ultrasonic pulses." Thesis, University of Aberdeen, 1990. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU024863.

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The development of a surface texture evaluation technique for the study of roughnesses of the order of a few microns using the signal processing of ultrasonic pulse-echo signals is described. The technique of extracting surface information by means of deconvolution is introduced. Strictly, a solution to the deconvolution problem normally does not exist or is not unique. The chosen method of approaching a solution is by the nonlinear Maximum Entropy Method (MEM), which offers superior image quality over many other filters. The algorithm is described and translated into a standalone computer pro
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23

Wang, Yuanxun. "Radar signature prediction and feature extraction using advanced signal processing techniques /." Digital version accessible at:, 1999. http://wwwlib.umi.com/cr/utexas/main.

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24

SANTOS, JÚNIOR Gutemberg Gonçalves dos. "Redução de ruído para sistemas de reconhecimento de voz utilizando subespaços vetoriais." Universidade Federal de Campina Grande, 2009. http://dspace.sti.ufcg.edu.br:8080/jspui/handle/riufcg/1508.

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Submitted by Johnny Rodrigues (johnnyrodrigues@ufcg.edu.br) on 2018-08-20T20:10:09Z No. of bitstreams: 1 GUTEMBERG GONÇALVES DOS SANTOS JÚNIOR - DISSERTAÇÃO PPGEE 2009..pdf: 2756190 bytes, checksum: 5812d37f7ad4c18eb26e9672d4890812 (MD5)<br>Made available in DSpace on 2018-08-20T20:10:09Z (GMT). No. of bitstreams: 1 GUTEMBERG GONÇALVES DOS SANTOS JÚNIOR - DISSERTAÇÃO PPGEE 2009..pdf: 2756190 bytes, checksum: 5812d37f7ad4c18eb26e9672d4890812 (MD5) Previous issue date: 2009-05-08<br>O estabelecimento de uma interface de comunicação através da voz entre seres humanos e computadores vem sendo pe
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25

Osanlou, Ardeshir. "Soft computing and fractal geometry in signal processing and pattern recognition." Thesis, De Montfort University, 2000. http://hdl.handle.net/2086/4242.

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26

Elvira, Jose M. "Neural networks for speech and speaker recognition." Thesis, Staffordshire University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.262314.

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27

El, Malki Karim. "A novel approach to high quality voice using echo cancellation and silence detection." Thesis, University of Sheffield, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.286579.

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28

Hartley, David Andrew. "Image correlation using digital signal processors." Thesis, Liverpool John Moores University, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304465.

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29

Jalalinajafabadi, Farideh. "Computerised GRBAS assessement of voice quality." Thesis, University of Manchester, 2016. https://www.research.manchester.ac.uk/portal/en/theses/computerised-grbas-assessement-of-voice-quality(7efd3263-b109-4137-87cf-b9559c61730b).html.

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Vocal cord vibration is the source of voiced phonemes in speech. Voice quality depends on the nature of this vibration. Vocal cords can be damaged by infection, neck or chest injury, tumours and more serious diseases such as laryngeal cancer. This kind of physical damage can cause loss of voice quality. To support the diagnosis of such conditions and also to monitor the effect of any treatment, voice quality assessment is required. Traditionally, this is done ‘subjectively’ by Speech and Language Therapists (SLTs) who, in Europe, use a well-known assessment approach called ‘GRBAS’. GRBAS is an
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30

DeVilliers, Edward Michael. "Implementing voice recognition and natural language processing in the NPSNET networked virtual environment." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 1996. http://handle.dtic.mil/100.2/ADA320340.

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Thesis (M.S. in Computer Science) Naval Postgraduate School, September 1996.<br>Thesis advisor(s): Nelson D. Ludlow, John S. Falby. "September 1996." Includes bibliographical references (p. 171-175). Also available online.
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31

Calitz, Wietsche Roets. "Independent formant and pitch control applied to singing voice." Thesis, Stellenbosch : University of Stellenbosch, 2004. http://hdl.handle.net/10019.1/16267.

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Thesis (MScIng)--University of Stellenbosch, 2004.<br>ENGLISH ABSTRACT: A singing voice can be manipulated artificially by means of a digital computer for the purposes of creating new melodies or to correct existing ones. When the fundamental frequency of an audio signal that represents a human voice is changed by simple algorithms, the formants of the voice tend to move to new frequency locations, making it sound unnatural. The main purpose is to design a technique by which the pitch and formants of a singing voice can be controlled independently.<br>AFRIKAANSE OPSOMMING: Onafhanklike fo
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32

Yiu, Siu Fung. "Recursive state-space approach to Ground Probing Radar signal processing." Thesis, Lancaster University, 1987. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.278379.

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33

Zhu, Yong. "Digital signal and image processing techniques for ultrasonic nondestructive evaluation." Thesis, City University London, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.336431.

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34

Ansourian, Megeurditch N. "Digital signal processing for the analysis of fetal breathing movements." Thesis, University of Edinburgh, 1989. http://hdl.handle.net/1842/13595.

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35

Chan, Arthur Yu Chung. "Robust speech recognition against unknown short-time noise /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202002%20CHAN.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002.<br>Includes bibliographical references (leaves 119-125). Also available in electronic version. Access restricted to campus users.
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36

Smith, Quentin D. "Multichannel Digital Signal Processor Based Red/Black Keyset." International Foundation for Telemetering, 1992. http://hdl.handle.net/10150/611927.

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International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California<br>This paper addresses a method to provide both secure and non-secure voice communications to a DS-1 network from a common keyset. In order to comply with both the electrical isolation requirements and the operational security issues regarding voice communications, an all-digital approach to the keyset was developed based upon the AD2101 DSP. Protocols that are handled by the keyset include: Multiple PTT modes, hot mike, telephone access, priority overr
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37

Nylén, Helmer. "Detecting Signal Corruptions in Voice Recordings for Speech Therapy." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-291429.

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When recording voice samples from a patient in speech therapy the quality of the recording may be affected by different signal corruptions, for example background noise or clipping. The equipment and expertise required to identify small disturbances are not always present at smaller clinics. Therefore, this study investigates possible machine learning algorithms to automatically detect selected corruptions in speech signals, including infrasound and random muting. Five algorithms are analyzed: kernel substitution based Support Vector Machine, Convolutional Neural Network, Long Short-term Memor
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38

Vemulapalli, Smita. "Audio-video based handwritten mathematical content recognition." Diss., Georgia Institute of Technology, 2012. http://hdl.handle.net/1853/45958.

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Recognizing handwritten mathematical content is a challenging problem, and more so when such content appears in classroom videos. However, given the fact that in such videos the handwritten text and the accompanying audio refer to the same content, a combination of video and audio based recognizer has the potential to significantly improve the content recognition accuracy. This dissertation, using a combination of video and audio based recognizers, focuses on improving the recognition accuracy associated with handwritten mathematical content in such videos. Our approach makes use of a video
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39

Loscos, Àlex. "Spectral processing of the singing voice." Doctoral thesis, Universitat Pompeu Fabra, 2007. http://hdl.handle.net/10803/7542.

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Aquesta tesi doctoral versa sobre el processament digital de la veu cantada, més concretament, sobre l'anàlisi, transformació i síntesi d'aquets tipus de veu en el domini espectral, amb especial èmfasi en aquelles tècniques rellevants per al desenvolupament d'aplicacions musicals.<br/><br/>La tesi presenta nous procediments i formulacions per a la descripció i transformació d'aquells atributs específicament vocals de la veu cantada. La tesis inclou, entre d'altres, algorismes per l'anàlisi i la generació de desordres vocals como ara rugositat, ronquera, o veu aspirada, detecció i modificació
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40

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

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This thesis presents novel techniques for the reduction of audio recordings and signal processing techniques as part of cough recognition. Evidence collected shows the reduction technique to be effective and the recognition techniques to give consistent performance across different patients. Cough is one of the commonest symptoms reported by patients to GPs. Despite this, it remains a significantly unmet medical need. At present, there exists no practical and validated technique for assessing the efficacy of therapies to treat cough on a large enough scale. Research that is presently undertake
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41

Schelinski, Stefanie. "Mechanisms of Voice Processing: Evidence from Autism Spectrum Disorder." Doctoral thesis, Humboldt-Universität zu Berlin, 2018. http://dx.doi.org/10.18452/19091.

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Die korrekte Wahrnehmung stimmlicher Information ist eine Grundvoraussetzung erfolgreicher zwischenmenschlicher Kommunikation. Die Stimme einer anderen Person liefert Information darüber wer spricht (Sprechererkennung), was gesagt wird (stimmliche Spracherkennung) und über den emotionalen Zustand einer Person (stimmliche Emotionserkennung). Autismus Spektrum Störungen (ASS) sind mit Einschränkungen in der Sprechererkennung und der stimmlichen Emotionserkennung assoziiert, während die Wahrnehmung stimmlicher Sprache relativ intakt ist. Die zugrunde liegenden Mechanismen dieser Einschränkungen s
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42

Sukittanon, Somsak. "Modulation scale analysis : theory and application for nonstationary signal classification /." Thesis, Connect to this title online; UW restricted, 2004. http://hdl.handle.net/1773/5875.

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43

Bakheet, Mohammed. "Improving Speech Recognition for Arabic language Using Low Amounts of Labeled Data." Thesis, Linköpings universitet, Institutionen för datavetenskap, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-176437.

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The importance of Automatic Speech Recognition (ASR) Systems, whose job is to generate text from audio, is increasing as the number of applications of these systems is rapidly going up. However, when it comes to training ASR systems, the process is difficult and rather tedious, and that could be attributed to the lack of training data. ASRs require huge amounts of annotated training data containing the audio files and the corresponding accurately written transcript files. This annotated (labeled) training data is very difficult to find for most of the languages, it usually requires people to p
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44

Kwok, Kwok Sai. "Algorithms for image segmentation and their applications to video signal processing." Thesis, Imperial College London, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.244298.

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45

Birkenes, Øystein. "A Framework for Speech Recognition using Logistic Regression." Doctoral thesis, Norwegian University of Science and Technology, Faculty of Information Technology, Mathematics and Electrical Engineering, 2007. http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-1599.

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<p>Although discriminative approaches like the support vector machine or logistic regression have had great success in many pattern recognition application, they have only achieved limited success in speech recognition. Two of the difficulties often encountered include 1) speech signals typically have variable lengths, and 2) speech recognition is a sequence labeling problem, where each spoken utterance corresponds to a sequence of words or phones.</p><p>In this thesis, we present a framework for automatic speech recognition using logistic regression. We solve the difficulty of variable length
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46

Faubel, Friedrich [Verfasser], and Dietrich [Akademischer Betreuer] Klakow. "Statistical signal processing techniques for robust speech recognition / Friedrich Faubel. Betreuer: Dietrich Klakow." Saarbrücken : Saarländische Universitäts- und Landesbibliothek, 2016. http://d-nb.info/1090875703/34.

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47

Meyer, Georg. "Models of neurons in the ventral cochlear nucleus : signal processing and speech recognition." Thesis, Keele University, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334715.

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48

Gooch, Richard M. "Machine learning techniques for signal processing, pattern recognition and knowledge extraction from examples." Thesis, University of Bristol, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.294898.

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49

健紘, 大田, and Kenko Ota. "Studies in signal processing for robust speech recognition in noisy and reverberant environments." Thesis, https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB10268908/?lang=0, 2008. https://doors.doshisha.ac.jp/opac/opac_link/bibid/BB10268908/?lang=0.

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50

Chai, Xiaoyong. "Sensor-based multiple-goal recognition /." View abstract or full-text, 2005. http://library.ust.hk/cgi/db/thesis.pl?COMP%202005%20CHAI.

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