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Sturt, Christian. "Pitch synchronous speech coding techniques." Thesis, University of Surrey, 2003. http://epubs.surrey.ac.uk/843327/.
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Efficient source coding techniques are necessary to make optimal use of the limited bandwidth available in mobile phone networks. Most current mobile telephone communication systems compress the speech waveform by using speech coders based on the Code Excited Linear Prediction (CELP) model. Such coders give high quality speech at bit rates of 8 kbps and above. Below 8 kbps, the quality of the coded speech degrades rapidly. At rates of 6 kbps and below, parametric speech coders offer better speech quality. These coders reduce the required bit rate by transmitting certain characteristics of the speech waveform to the decoder, rather than attempting to code the waveform itself. The disadvantage of parametric coders is that the maximum achievable quality is limited by assumptions made during the coding of the speech signal. The aim of the research presented is to investigate and eliminate the factors that limit the speech quality of parametric coders. A new pitch synchronous coding model is proposed that operates on individual pitch cycle waveforms of speech rather than longer, fixed length frames as used in classic techniques. In order to implement a pitch synchronous coder, new pitch cycle detection algorithms have been proposed. Pitch synchronous parameter analysis was investigated and several new techniques have been developed. A novel pitch synchronous split-band voicing estimator has been proposed that utilises only the phase of the speech harmonics rather than the periodicity used in traditional techniques. Fixed rate quantisation of pitch synchronous speech parameters has been investigated and a joint quantisation/interpolation scheme has been proposed. This scheme has been applied to the quantisation of the pitch synchronous parameters and has been shown to outperform traditional quantisation techniques. A comparison of a reference parametric coder with its pitch synchronous counterpart has shown that the pitch synchronous paradigm eliminates some of the main factors that limit the speech quality in parametric coders. It is expected that this will lead to the development of speech coders that can produce speech of higher quality than current parametric coders operating at the same bit rate. Key words: Speech Coding, Pitch Synchronous, Sinusoidal Coding, Split-Band LPC Coding.
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Burnett, I. S. "Hybrid techniques for speech coding." Thesis, University of Bath, 1992. https://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.317353.
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Sidorova, Julia. "Optimization techniques for speech emotion recognition." Doctoral thesis, Universitat Pompeu Fabra, 2009. http://hdl.handle.net/10803/7575.
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Hay tres aspectos innovadores. Primero, un algoritmo novedoso para calcular el contenido emocional de un enunciado, con un diseño mixto que emplea aprendizaje estadístico e información sintáctica. Segundo, una extensión para selección de rasgos que permite adaptar los pesos y así aumentar la flexibilidad del sistema. Tercero, una propuesta para incorporar rasgos de alto nivel al sistema. Dichos rasgos, combinados con los rasgos de bajo nivel, permiten mejorar el rendimiento del sistema.<br>The first contribution of this thesis is a speech emotion recognition system called the ESEDA capable of recognizing emotions in di®erent languages. The second contribution is the classifier TGI+. First objects are modeled by means of a syntactic method and then, with a statistical method the mappings of samples are classified, not their feature vectors. The TGI+ outperforms the state of the art top performer on a benchmark data set of acted emotions. The third contribution is high-level features, which are distances from a feature vector to the tree automata accepting class i, for all i in the set of class labels. The set of low-level features and the set of high-level features are concatenated and the resulting set is submitted to the feature selection procedure. Then the classification step is done in the usual way. Testing on a benchmark dataset of authentic emotions showed that this classification strategy outperforms the state of the art top performer.
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Al-Naimi, Khaldoon Taha. "Advanced speech processing and coding techniques." Thesis, University of Surrey, 2002. http://epubs.surrey.ac.uk/843488/.
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Over the past two decades there has been substantial growth in speech communications and new speech related applications. Bandwidth constraints led researchers to investigate ways of compressing speech signals whilst maintaining speech quality and intelligibility so as to increase the possible number of customers for the given bandwidth. Because of this a variety of speech coding techniques have been proposed over this period. At the heart of any proposed speech coding method is quantisation of the speech production model parameters that need to be transmitted to the decoder. Quantisation is a controlling factor for the targeted bit rates and for meeting quality requirements. The objectives of the research presented in this thesis are twofold. The first enabling the development of a very low bit rate speech coder which maintains quality and intelligibility. This includes increasing the robustness to various operating conditions as well as enhancing the estimation and improving the quantisation of speech model parameters. The second objective is to provide a method for enhancing the performance of an existing speech related application. The first objective is tackled with the aid of three techniques. Firstly, various novel estimation techniques are proposed which are such that the resultant estimated speech production model parameters have less redundant information and are highly correlated. This leads to easier quantisation (due to higher correlation) and therefore to bit saving. The second approach is to make use of the joint effect of the quantisation of spectral parameters (i.e. LSF and spectral amplitudes) for their big impact on the overall bit allocation required. Work towards the first objective also includes a third technique which enhances the estimation of a speech model parameter (i.e. the pitch) through a robust statistics-based post-processing (or tracking) method which operates in noise contaminated environments. Work towards the second objective focuses on an application where speech plays an important role, namely echo-canceller and noise-suppressor systems. A novel echo-canceller method is proposed which resolves most of the weaknesses present in existing echo-canceller systems and improves the system performance.
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Tomita, Masaru. "Sentence Analysis Techniques in Speech Translation." Kyoto University, 1994. http://hdl.handle.net/2433/160745.
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本文データは平成22年度国立国会図書館の学位論文(博士)のデジタル化実施により作成された画像ファイルを基にpdf変換したものである<br>Kyoto University (京都大学)<br>0048<br>新制・論文博士<br>博士(工学)<br>乙第8652号<br>論工博第2893号<br>新制||工||968(附属図書館)<br>UT51-94-R411<br>(主査)教授 長尾 真, 教授 堂下 修司, 教授 池田 克夫<br>学位規則第4条第2項該当
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Farooq, Omar. "Wavelet-based techniques for speech recognition." Thesis, Loughborough University, 2002. https://dspace.lboro.ac.uk/2134/34229.
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In this thesis, new wavelet-based techniques have been developed for the extraction of features from speech signals for the purpose of automatic speech recognition (ASR). One of the advantages of the wavelet transform over the short time Fourier transform (STFT) is its capability to process non-stationary signals. Since speech signals are not strictly stationary the wavelet transform is a better choice for time-frequency transformation of these signals. In addition it has compactly supported basis functions, thereby reducing the amount of computation as opposed to STFT where an overlapping window is needed.
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Hassanain, Elham. "Novel cepstral techniques applied to speech synthesis." Thesis, University of Surrey, 2006. http://epubs.surrey.ac.uk/842745/.
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The aim of this research was to develop an improved analysis and synthesis model for utilization in speech synthesis. Conventionally, linear prediction has been used in speech synthesis but is restricted by the requirement of an all-pole, minimum phase model. Here, cepstral homomorphic deconvolution techniques were used to approach the problem, since there are fewer constraints on the model and some evidence in the literature that shows that cepstral homomorphic deconvolution can give improved performance. Specifically the spectral root cepstrum was developed in an attempt to separate the magnitude and phase spectra. Analysis and synthesis filters were developed on these two data streams independently in an attempt to improve the process. It is shown that independent analysis of the magnitude and phase spectra is preferable to a combined analysis, and so the concept of a phase cepstrum is introduced, and a number of different phase cepstra are defined. Although extremely difficult for many types of signals, phase analysis via a root cepstrum and the Hartley phase cepstrum give encouraging results for a wide range of both minimum and maximum phase signals. Overall, this research has shown that improved synthesis can be achieved with these techniques.
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Edge, James D. "Techniques for the synthesis of visual speech." Thesis, University of Sheffield, 2004. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.419276.
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Leidal, Kenneth (Kenneth Knute). "Neural techniques for modeling visually grounded speech." Thesis, Massachusetts Institute of Technology, 2018. http://hdl.handle.net/1721.1/119562.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2018.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 103-107).<br>In this thesis, I explore state of the art techniques for using neural networks to learn semantically-rich representations for visual and audio data. In particular, I analyze and extend the model introduced by Harwath et al. (2016), a neural architecture which learns a non-linear similarity metric between images and audio captions using sampled margin rank loss. In Chapter 1, I provide a background on multimodal learning and motivate the need for further research in the area. In addition, I give an overview of Harwath et al. (2016)'s model, variants of which will be used throughout the rest of the thesis. In Chapter 2, I present a quantitative and qualitative analysis of the modality retrieval behavior of the state of the art architecture used by Harwath et al. (2016), identifying a bias towards certain examples and proposing a solution to counteract that bias. In Chapter 3, I introduce the property of modality invariance and explain a regularization technique I created to promote this property in learned semantic embedding spaces. In Chapter 4, I apply the architecture to a new dataset containing videos, which offers unique opportunities to include temporal visual data and ambient audio unavailable in images. In addition, the video domain presents new challenges, as the data density increases with the additional time dimension. I conclude with a discussion about multimodal learning, language acquisition, and unsupervised learning in general.<br>by Kenneth Leidal.<br>M. Eng.
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Jevtić, Nikola. "Estimation and modeling techniques for speech recognition /." Diss., Connect to a 24 p. preview or request complete full text in PDF format. Access restricted to UC campuses, 2005. http://wwwlib.umi.com/cr/ucsd/fullcit?p3167817.
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Principi, Emanuele, and Emanuele Principi. "Pre-processing techniques for automatic speech recognition." Doctoral thesis, Università Politecnica delle Marche, 2009. http://hdl.handle.net/11566/242152.
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Akin, Faith W., and Owen D. Murnane. "Advanced Techniques in Vestibular Assessment." Digital Commons @ East Tennessee State University, 2007. https://dc.etsu.edu/etsu-works/1943.
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Sakuma, Jun’ichi. "On the Tripartite System of Case Marking in the Finnish Language." School of Letters, Nagoya University, 2014. http://hdl.handle.net/2237/19780.
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Akdemir, Eren. "Bimodal Automatic Speech Segmentation And Boundary Refinement Techniques." Phd thesis, METU, 2010. http://etd.lib.metu.edu.tr/upload/3/12611732/index.pdf.
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Automatic segmentation of speech is compulsory for building large speech databases to be used in speech processing applications. This study proposes a bimodal automatic speech segmentation system that uses either articulator motion information (AMI) or visual information obtained by a camera in collaboration with auditory information. The presence of visual modality is shown to be very beneficial in speech recognition applications, improving the performance and noise robustness of those systems. In this dissertation a significant increase in the performance of the automatic speech segmentation system is achieved by using a bimodal approach.
Automatic speech segmentation systems have a tradeoff between precision and resulting number of gross errors. Boundary refinement techniques are used in order to increase precision of these systems without decreasing the system performance. Two novel boundary refinement techniques are proposed in this thesis<br>a hidden Markov model (HMM) based fine tuning system and an inverse filtering based fine tuning system. The segment boundaries obtained by the bimodal speech segmentation system are improved further by using these techniques.
To fulfill these goals, a complete two-stage automatic speech segmentation system is produced and tested in two different databases. A phonetically rich Turkish audiovisual speech database, that contains acoustic data and camera recordings of 1600 Turkish sentences uttered by a male speaker, is build from scratch in order to be used in the experiments. The visual features of the recordings are extracted and manual phonetic alignment of the database is done to be used as a ground truth for the performance tests of the automatic speech segmentation systems.
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Ping, Hui. "Isolated word speech recognition using fuzzy neural techniques." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 2000. http://www.collectionscanada.ca/obj/s4/f2/dsk1/tape4/PQDD_0019/MQ52633.pdf.
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Gales, Mark John Francis. "Model-based techniques for noise robust speech recognition." Thesis, University of Cambridge, 1995. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.319311.
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Cox, S. J. "Techniques for rapid speaker adaptation in speech recognition." Thesis, University of East Anglia, 1998. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267271.
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Crozier, Philip Mark. "Enhancement techniques for noise affected telephone quality speech." Thesis, University of Liverpool, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.321115.
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Mustapha, Azhar K. 1975. "Postfiltering techniques in low bit-rate speech coders." Thesis, Massachusetts Institute of Technology, 1999. http://hdl.handle.net/1721.1/80589.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1999.<br>Includes bibliographical references (leaves 78-80).<br>by Azhar K. Mustapha.<br>M.Eng.
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Chuangsuwanich, Ekapol. "Multilingual techniques for low resource automatic speech recognition." Thesis, Massachusetts Institute of Technology, 2016. http://hdl.handle.net/1721.1/105571.
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Thesis: Ph. D., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2016.<br>This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.<br>Cataloged from student-submitted PDF version of thesis.<br>Includes bibliographical references (pages [133]-143).<br>Out of the approximately 7000 languages spoken around the world, there are only about 100 languages with Automatic Speech Recognition (ASR) capability. This is due to the fact that a vast amount of resources is required to build a speech recognizer. This often includes thousands of hours of transcribed speech data, a phonetic pronunciation dictionary or lexicon which spans all words in the language, and a text collection on the order of several million words. Moreover, ASR technologies usually require years of research in order to deal with the specific idiosyncrasies of each language. This makes building a speech recognizer on a language with few resources a daunting task. In this thesis, we propose a universal ASR framework for transcription and keyword spotting (KWS) tasks that work on a variety of languages. We investigate methods to deal with the need of a pronunciation dictionary by using a Pronunciation Mixture Model that can learn from existing lexicons and acoustic data to generate pronunciation for new words. In the case when no dictionary is available, a graphemic lexicon provides comparable performance to the expert lexicon. To alleviate the need for text corpora, we investigate the use of subwords and web data which helps im- prove KWS spotting results. Finally, we reduce the need for speech recordings by using bottleneck (BN) features trained on multilingual corpora. We first propose the Low-rank Stacked Bottleneck architecture which improves ASR performance over previous state-of-the-art systems. We then investigate a method to select data from various languages that is most similar to the target language in a data-driven manner, which helps improve the eectiveness of the BN features. Using techniques described and proposed in this thesis, we are able to more than double the KWS performance for a low-resource language compared to using standard techniques geared towards rich resource domains.<br>by Ekapol Chuangsuwanich.<br>Ph. D.
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De, Nardo Thales. "Listener Responses to Speech Modification Techniques for Stuttering." Thesis, University of Louisiana at Lafayette, 2017. http://pqdtopen.proquest.com/#viewpdf?dispub=10266951.
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<p> The purpose of this study was to explore how listeners perceived adults who use speech modification techniques for stuttering and how these techniques affect listener comfort. Eighty-nine university undergraduate students completed Likert-type scales and answered descriptive questions to rated four audio samples presenting stuttered speech, prolonged speech, speech with pull-outs, and speech with preparatory-sets.</p><p> The results of the scales reveled that listeners perceived the use of preparatory-sets to be a significantly more natural and less handicapping form of speech than the other experimental conditions. No significant differences were found in personality judgments of the speaker. However, all four conditions were rated to have an overwhelmingly negative impression, which was primarily described with negative communication and personality attributes.</p><p> Listener comfort was significant more positive in the preparatory-set condition than the other conditions and in the stuttered speech condition compared to the prolonged speech condition. Most participants reported that listener comfort was influenced by the negative speech attributes of each condition, which varied across conditions. The participants were significantly less willing to socially interact with the speakers using prolonged speech. </p><p> The results of this investigation supported the use of preparatory-sets to increase perceived speech naturalness, listener comfort, and to decrease perceived handicap. The use of prolonged speech at reduced speech rates should be used with caution as it can lead to increased negative socially interaction and listener comfort. However, all the speech conditions were rated more negatively than the norms for fluent speech. Therefore, counseling and desensitization techniques should be incorporated in interventions for stuttering.</p><p>
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Champion, Pierre. "Anonymizing Speech : Evaluating and Designing Speaker Anonymization Techniques." Electronic Thesis or Diss., Université de Lorraine, 2023. http://www.theses.fr/2023LORR0101.
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L'essor de l'utilisation d'assistants vocaux, présents dans les téléphones, automobiles et autres, a augmenté la quantité de données de parole collectées et stockées. Bien que cette collecte de données soit cruciale pour entrainer les modèles qui traitent la parole, cette collecte soulève également des préoccupations de protection de la vie privée. Des technologies de pointe traitant la parole, telles que le clonage vocal et la reconnaissance d'attributs personnels (telles que l'identité, l'émotion, l'âge, le genre, etc.), peuvent être exploitées pour accéder et utiliser des informations personnelles. Par exemple, un malfaiteur pourrait utiliser le clonage vocal pour se faire passer pour une autre personne afin d'obtenir un accès non autorisé à ses informations bancaires par téléphone. Avec l'adoption croissante des assistants vocaux tels qu'Alexa, Google Assistant et Siri, et la facilité avec laquelle les données peuvent être collectées et stockées, le risque d'utilisation abusive de technologies telles que le clonage vocal et la reconnaissance d'attributs personnels augmente. Il est donc important pour les entreprises et les organisations de prendre en compte ces risques et de mettre en place des mesures appropriées pour protéger les données des utilisateurs, en conformité avec les réglementations juridiques telles que le Règlement Général sur la Protection des Données (RGPD). Pour répondre aux enjeux liés à la protection de la vie privée, cette thèse propose des solutions permettant d'anonymiser la parole. L'anonymisation désigne ici le processus consistant à rendre les signaux de parole non associables à une identité spécifique, tout en préservant leur utilité, c'est-à-dire ne pas modifier le contenu linguistique du message. L'objectif est de préserver la vie privée des individus en éliminant ou en rendant floues toutes les informations personnellement identifiables (PPI) contenues dans le signal acoustique, telles que l'accent ou le style de parole d'une personne. Les informations linguistiques personnelles telles que numéros de téléphone ou noms de personnes ne font pas partie du champ d'étude de cette thèse. Notre recherche s'appuie sur les méthodes d'anonymisation existantes basées sur la conversion de la voix et sur des protocoles d'évaluation existants. Nous commençons par identifier et expliquer plusieurs défis auxquels les protocoles d'évaluation doivent faire face afin d'évaluer de manière précise le niveau de protection de la vie privée. Nous clarifions comment les systèmes d'anonymisation doivent être configurés pour être correctement évalués, en soulignant le fait que de nombreuses configurations ne permettent pas une évaluation adéquate de non-asociabilité d'un signal a une identité. Nous étudions et examinons également le système d'anonymisation basé sur la conversion de la voix le plus courant, identifions ses points faibles, et proposons de nouvelles méthodes pour en améliorer les performances. Nous avons isolé tous les composants du système d'anonymisation afin d'évaluer le niveau de PPI encodé par chaque composant. Ensuite, nous proposons plusieurs méthodes de transformation de ces composants dans le but de réduire autant que possible les PPI encodées, tout en maintenant l'utilité. Nous promouvons les algorithmes d'anonymisation basés sur l'utilisation de la quantification en alternative à la méthode la plus utilisée et la plus connue basée sur le bruit. Enfin, nous proposons une nouvelle méthode d'évaluation qui vise à inverser l'anonymisation, créant ainsi une nouvelle manière d'étudier les systèmes d'anonymisation<br>The growing use of voice user interfaces, from telephones to remote controls, automobiles, and digital assistants, has led to a surge in the collection and storage of speech data. While data collection allows for the development of efficient tools powering most speech services, it also poses serious privacy issues for users as centralized storage makes private personal speech data vulnerable to cyber threats. Advanced speech technologies, such as voice-cloning and personal attribute recognition, can be used to access and exploit sensitive information. Voice-cloning technology allows an attacker to take a recording of a person's voice and use it to generate new speech that sounds like it is coming from that person. For example, an attacker could use voice-cloning to impersonate a person's voice to gain unauthorized access to his/her financial information over the phone. With the increasing use of voice-based digital assistants like Amazon's Alexa, Google's Assistant, and Apple's Siri, and with the increasing ease with which personal speech data can be collected and stored, the risk of malicious use of voice-cloning and speaker/gender/pathological/etc. recognition technologies have increased. Companies and organizations need to consider these risks and implement appropriate measures to protect user data in order to prevent misuse of speech technologies and comply with legal regulations (e.g., General Data Protection Regulation (GDPR)). To address these concerns, this thesis proposes solutions for anonymizing speech and evaluating the degree of the anonymization. In this work, anonymization refers to the process of making personal speech data unlinkable to an identity, while maintaining the usefulness (utility) of the speech signal (e.g., access to the linguistic content). The goal is to protect the privacy of individuals by removing or obscuring any Personally Identifiable Information (PPI) from the acoustic of speech. PPI includes things like a person's voice, accent, and speaking style; other personal information in the speech content like, phone number, person name, etc., is out of the scope of this thesis. Our research is built on top of existing anonymization methods based on voice conversion and existing evaluation protocols. We start by identifying and explaining several challenges that evaluation protocols need to consider to evaluate the degree of privacy protection properly. We clarify how anonymization systems need to be configured for evaluation purposes and highlight the fact that many practical deployment configurations do not permit privacy evaluation. Furthermore, we study and examine the most common voice conversion-based anonymization system and identify its weak points, before suggesting new methods to overcome some limitations. We isolate all components of the anonymization system to evaluate the degree of speaker PPI associated with each of them. Then, we propose several transformation methods for each component to reduce as much as possible speaker PPI while maintaining utility. We promote anonymization algorithms based on quantization-based transformation as an alternative to the most-used and well-known noise-based approach. Finally, we endeavor a new attack method to invert the anonymization, creating a new threat. In this thesis, we openly work on sharing anonymization systems and evaluation protocols to aid organizations in facilitating the preservation of privacy rights for individuals
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Akin, Faith W., Owen D. Murnane, J. Tampas, and C. Clinard. "A Comparison of VEMP Recording Techniques." Digital Commons @ East Tennessee State University, 2005. https://dc.etsu.edu/etsu-works/1905.
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Larreategui, Mikel. "High-quality text-to-speech synthesis using sinusoidal techniques." Thesis, Staffordshire University, 1996. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.309790.
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Burianek, Theresa K. (Theresa Kathleen) 1977. "Building a speech understanding system using word spotting techniques." Thesis, Massachusetts Institute of Technology, 2000. http://hdl.handle.net/1721.1/81552.
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Thesis (M.Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2000.<br>Includes bibliographical references (p. 63-65).<br>by Theresa K. Burianek.<br>M.Eng.
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Nock, Harriet Jane. "Techniques for modelling phonological processes in automatic speech recognition." Thesis, University of Cambridge, 2001. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.621360.
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Farsi, Hassan. "Advanced pre-and-post processing techniques for speech coding." Thesis, University of Surrey, 2003. http://epubs.surrey.ac.uk/844491/.
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Advances in digital technology in the last decade have motivated the development of very efficient and high quality speech compression algorithms. While in the early low bit rate coding systems, the main target was the production of intelligible speech at low bit rates, expansion of new applications such as mobile satellite systems increased the demand for reducing the transmission bandwidth and achieving higher speech quality. This resulted in the development of efficient parametric models for speech production system. These models were the basis of powerful speech compression algorithms such as CELP, MBE, MELP and WI. The performance of a speech coder not only depends on the speech production model employed but also on the accurate estimation of speech parameters. Periodicity, also known as pitch, is one of the speech parameters that greatly affect the synthesised speech quality. Thus, the subject of pitch determination has attracted much research in the area of low bit rate coding. In these studies it is assumed that for a short segment of speech, called frame, the pitch is fixed or smoothly evolving. The pitch estimation algorithms generally fail to determine irregular variations, which can occur at onset and offset speech segments. In order to overcome this problem, a novel preprocessing method, which detects irregular pitch variations and modifies the speech signal such as to improve the accuracy of the pitch estimation, is proposed. This method results in more regular speech while maintaining perceptual speech quality. The perceptual quality of the synthesised speech may also be improved using postfiltering techniques. Conventional postfiltering methods generally consider the enhancement of the whole speech spectrum. This may result in the broadening of the first formant, which leads to the increase of quantisation noise for this formant. A new postfiltering technique, which is based on factorising the linear prediction synthesis filter, is proposed. This provides more control over the formant bandwidth and attenuation of spectral speech valleys. Key words: Pitch smoothing, speech pre-processor, postfiltering.
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Oger, Marie. "Model-based techniques for flexible speech and audio coding." Nice, 2007. http://www.theses.fr/2007NICE4109.
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L’objectif de cette thèse est de développer des techniques de codage de parole et audio optimales et plus flexibles que avec l’état de l’art, pouvant s’adapter en temps réel à différentes contraintes (débit, largeur de bande, retard). Cette problématique est étudiée à l’aide de différents outils : modélisation statistique, théorie de la quantification à haut débit, codage entropique flexible. On propose d’abord une nouvelle technique de codage flexible des coefficients de prédiction linéaire (LPC) combinant une transformée de Karhumen-Loeve (KLT) et une quantification scalaire basée sur un modèle gaussien généralisé. Les performances sont équivalentes à celle du quantificateur utilisé dans l’AMR-WB. De plus la complexité est moindre. Puis, on propose deux techniques de codage audio par transformée flexible, l’une utilisant le codage « stack-run » et l’autre le codage par plans de bits basé modèle. Dans les deux cas, le signal après pondération perceptuelle et transformation discrète en cosinus modifié (MDCT) est modélisé par une distribution gaussienne généralisée qui sert à optimiser le codage. La qualité du codeur stack-run est meilleure que ITU-T G. 722. 1 à bas débit et équivalente à haut débit. Par contre, le codeur stack-run est plus complexe et son coût mémoire est faible. L’avantage du codage par plans de bits est d’être scalable en débit. Nous proposons d’utiliser le modèle gaussien généralisé afin d’initialiser les tables de probabilités du codage arithmétique utilisé dans le codage par plan de bits. La qualité associée est inférieure à celle du codeur stack-run à bas débit et équivalente à haut débit. Par contre, la complexité de calcul est proche de G. 722. 1<br>The objective of this thesis is to develop optimal speech and audio coding techniques which are more flexible than the state of the art and can adapt in real-time to various constraints (rate, bandwidth, delay). This problem is addressed using several tools : statistical models, high-rate quantization theory, flexible entropy coding. Firstly, a novel method of flexible coding for linear prediction coding (LPC) coefficients is proposed using Karhunen-Loeve transform (KLT) and scalar quantization based on generalized Gaussian modelling. This method has a performance equivalent to the LPC quantizer used in AMR-WB with a lower complexity. Then, two transform audio coding structures are proposed using either stack-run coding or model-based bit plane coding. In both case the coefficients after perceptual weighting and modified discrete cosine transform (MDCT) are approximated by a generalized Gaussian distribution. The coding of MDCT coefficients is optimized according to this model. The performance is compared with that of ITU-T G. 7222. 1. The stack-run coder is better than G. 7222. 1 at low bit rates and equivalent at high bit rates. However, the computational complexity of the proposed stack-run coder is higher and the memory requirement is low. The bit plane coder has the advantage of being bit rate scalable. The generalized Gaussian model is used to initialize the probability tables of an arithmetic coder. The bit plane coder is worse than stack-run coding at low bit rates and equivalent at high bit rates. It has a computational complexity close to G. 7222. 1 while memory requirement is still low
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King, Scott Alan. "A Facial Model and Animation Techniques for Animated Speech." The Ohio State University, 2001. http://rave.ohiolink.edu/etdc/view?acc_num=osu991423221.
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Oztoprak, Huseyin. "Advanced techniques for error robust audio and speech communications." Thesis, University of Surrey, 2011. http://epubs.surrey.ac.uk/843131/.
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The past decades have seen a very fast growth of the telecommunications industry. Mobile telephony has evolved from a specialist application to being commonplace and affordable, and is now a mass-market industry. Like mobile telephony, multimedia communications has also evolved, where voice, video and data are all to be integrated into one device. Today's audio and speech communication systems are characterised by heterogeneous networks, and varying natural environment conditions. The resilience of employed coding paradigms against network related problems is one of the principal factors in determining the satisfaction of end user. The aim of the research presented here is to improve the error resilience of audio and speech codecs using the dedicated redundancy in a source-aware way. Firstly, Index Assignment based Channel Coding (IACC), a joint source channel codec designed for alleviating the effects of bit errors on the speech and audio codecs is introduced. Although IACC is a type of joint source channel coding, it does not intervene with the source codec design. The proposed scheme takes into account source characteristics and adjusts the amount of coding according to the sensitivity of the different values of the source parameters. It is shown that source characteristics play an important role in the performance of IACC. A scheme which concatenates IACC and convolutional coding is also presented. The performance of IACC based schemes has been evaluated by applying them to the parameters generated by AMR-WB+ audio codec. A method for perceptual training of IACC codes is also proposed. Subjective tests comparing the performance of IACC based schemes and established convolutional coding have also been performed. Next, various new techniques for improving the performance of multiple description coding techniques in protecting audio in networks with packet losses are presented. AAC is chosen as the underlying audio codec. Firstly, two methods for improving the performance of multiple description transform coding in application to spectral coefficients are proposed. Secondly, multiple description vector quantisation is adapted to AAC spectral coefficients and a method for improving its performance is presented. Thirdly, a coding scheme which lowers the side information burden in multiple description coding is proposed. Lastly, the performance of techniques and single description coding are compared in networks with various packet loss rates. Useful operating points for all these schemes are obtained. A scalable multiple description scheme is introduced as the last contribution in the thesis. The proposed system provides multiple description for the hierarchical two layers. The trade-off between the first and second layers and the trade-off between the central and side distortions are controlled parametrically.
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Nahma, Lara. "A Study into Speech Enhancement Techniques in Adverse Environment." Thesis, Curtin University, 2018. http://hdl.handle.net/20.500.11937/76002.
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This dissertation developed speech enhancement techniques that improve the speech quality in applications such as mobile communications, teleconferencing and smart loudspeakers. For these applications it is necessary to suppress noise and reverberation. Thus the contribution in this dissertation is twofold: single channel speech enhancement system which exploits the temporal and spectral diversity of the received microphone signal for noise suppression and multi-channel speech enhancement method with the ability to employ spatial diversity to reduce reverberation.
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Akin, Faith W., J. Tampas, C. Clinard, and Owen D. Murnane. "A Comparison of VEMP Recording Techniques." Digital Commons @ East Tennessee State University, 2006. https://dc.etsu.edu/etsu-works/1898.
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Fábián, Tibor. "Confidence measurement techniques in automatic speech recognition and dialog management." Tönning Lübeck Marburg Der Andere Verl, 2008. http://d-nb.info/989056376/04.
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Jabloun, Firas. "Perceptual and Multi-Microphone Signal Subspace Techniques for Speech Enhancement." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=95577.
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The performance of speech communication systems, such as hands-free telephony, is known to seriously degrade under adverse acoustic environments. The presence of noise can lead to the loss of intelligibility as well as to the listener's fatigue. These problems can generally make the existing systems unsatisfactory to the customers especially that the offered services usually put no restrictions on where they can actually be used. For this reason, speech enhancement is vital for the overall success of these systems on the market.In this thesis we present new speech enhancement techniques based on the signal subspace approach. In this approach the input speech vectors are projected onto the signal subspace where it is processed to suppress any remaining noise then reconstructed again in the time domain. The projection is obtained via the eigenvalue decomposition of the speech signal covariance matrix.The main problem with the signal subspace based methods is the expensive eigenvalue decomposition. In this thesis we present a simple solution to this problem in which the signal subspace filter is updated at a reduced rate resulting in a significant reduction in the computational load. This technique exploits the stationarity of the input speech signal within a frame of 20-30 msec to use the same eigenvalue decomposition for several input vectors. The original implementation scheme was to update the signal subspace filter for every such input vector. The proposed technique was experimentally found to offer significant computational savings at almost no performance side-effects.The second contribution of this thesis is the incorporation of the human hearing properties in the signal subspace approach using a sophisticated masking model. It is known that there is a tradeoff between the amount of noise reduction achieved and the resulting signal distortion. Therefore, it would be beneficial to avoid suppressing any noise components as long as they are not perceived by the<br>Il est connu que la performance des systèmes de communication par la voix se détériore lorsqu'ils sont utilisés dans des environnements acoustiques peu favorables. En effet, la présence du bruit cause la perte de l'intelligibilité et engendre la fatigue chez les auditeurs. Ces problèmes peuvent rendre les systèmes existant sur le marché inintressants pour les clients surtout que les services offerts par les compagnies de télécommunication ne comportent aucune restriction sur les endroits où ils seront utilisés. Dans ce contexte, les algorithmes qui visent à améliorer la qualité du signal parole sont très importants du fait qu'ils permettent à ces systèmes de satisfaire les attentes du marché. Dans cette thèse, nous présentons des nouvelles techniques, visant à rehausser la qualité de la voix, qui sont basées sur l'approche de sous-espace du signal (SES). Selon cette approche, les vecteurs du signal sont projetés sur le sous-espace du signal où ils sont traités afin d'éliminer le bruit restant. Après ce traitement, les vecteurs seront reconstruits dans le domaine du temps. La projection est obtenue grâce à la décomposition en valeurs propres de la matrice de covariance du signal parole. Le problème avec l'approche SES est que le coût, en terme de temps de calcul, relié à la décomposition en valeurs propres est élevé. Dans cette thèse, nous proposons une technique simple pour résoudre ce problème. Cette technique réduit considérablement le temps de calcul car le filtre en sous-espace est mis à jour moins fréquemment. Initialement, l'implémentation de l'approche SES consistait à recalculer un nouveau filtre pour chaque vecteur. L'originalité de notre technique réside dans l'exploitation de la stationnarité du signal parole dans un intervalle de 20-30 msec afin d'utiliser la même décomposition en valeurs propres pour plusieurs vecteurs. Les expériences menées montrent que notre nouvelle technique réduit consid
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El-Maleh, Khaled Helmi. "Classification-based techniques for digital coding of speech-plus-noise." Thesis, McGill University, 2004. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=84239.
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With the increasing demand for wireless voice services and limited bandwidth resources, it is critical to develop and implement coding techniques which use spectrum efficiently. One approach to increasing system capacity is to lower the bit rate of telephone speech. A typical telephone conversation contains approximately 40% speech and 60% silence or background acoustic noise. A reduction of the average coding rate can be achieved by using a Voice Activity Detection (VAD) unit to distinguish speech from silence or background noise. The VAD decision can be used to select different coding modes for speech and noise or to discontinue transmission during speech pauses.<br>The quality of a telephone conversation using a VAD-based coding system depends on three major modules: the speech coder, the noise coder, and the VAD. Existing schemes for reduced-rate coding of background noise produce a signal that sounds different from the noise at the transmitting side. The frequent changes of the noise character between that produced during talk spurts (noise coded along with the speech) and that produced during speech pauses (noise coded at a reduced rate) are noticeable and can be annoying to the user.<br>The objective of this thesis is to develop techniques that enhance the output quality of variable-rate and discontinuous-transmission speech coding systems operating in noisy acoustic environments during the pauses between speech bursts. We propose novel excitation models for natural-quality reduced-rate coding of background acoustic noise in voice communication systems. A better representation of the excitation signal in a noise-synthesis model is achieved by classifying the type of acoustic environment noise. Class-dependent residual substitution is used at the receive side to synthesize a background noise that sounds similar to the background noise at the transmit side. The improvement in the quality of synthesized noise during speech gaps helps in preserving noise continuity between talk spurts and speech pauses, and enhances the overall perceived quality of a conversation.
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Edwards, Richard. "Advanced signal processing techniques for pitch synchronous sinusoidal speech coders." Thesis, University of Surrey, 2007. http://epubs.surrey.ac.uk/833/.
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Recent trends in commercial and consumer demand have led to the increasing use of multimedia applications in mobile and Internet telephony. Although audio, video and data communications are becoming more prevalent, a major application is and will remain the transmission of speech. Speech coding techniques suited to these new trends must be developed, not only to provide high quality speech communication but also to minimise the required bandwidth for speech, so as to maximise that available for the new audio, video and data services. The majority of current speech coders employed in mobile and Internet applications employ a Code Excited Linear Prediction (CELP) model. These coders attempt to reproduce the input speech signal and can produce high quality synthetic speech at bit rates above 8 kbps. Sinusoidal speech coders tend to dominate at rates below 6 kbps but due to limitations in the sinusoidal speech coding model, their synthetic speech quality cannot be significantly improved even if their bit rate is increased. Recent developments have seen the emergence and application of Pitch Synchronous (PS) speech coding techniques to these coders in order to remove the limitations of the sinusoidal speech coding model. The aim of the research presented in this thesis is to investigate and eliminate the factors that limit the quality of the synthetic speech produced by PS sinusoidal coders. In order to achieve this innovative signal processing techniques have been developed. New parameter analysis and quantisation techniques have been produced which overcome many of the problems associated with applying PS techniques to sinusoidal coders. In sinusoidal based coders, two of the most important elements are the correct formulation of pitch and voicing values from the' input speech. The techniques introduced here have greatly improved these calculations resulting in a higher quality PS sinusoidal speech coder than was previously available. A new quantisation method which is able to reduce the distortion from quantising speech spectral information has also been developed. When these new techniques are utilised they effectively raise the synthetic speech quality of sinusoidal coders to a level comparable to that produced by CELP based schemes, making PS sinusoidal coders a promising alternative at low to medium bit rates.
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Mann, Iain. "An investigation of nonlinear speech synthesis and pitch modification techniques." Thesis, University of Edinburgh, 2000. http://hdl.handle.net/1842/1378.
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Speech synthesis technology plays an important role in many aspects of man–machine interaction, particularly in telephony applications. In order to be widely accepted, the synthesised speech quality should be as human–like as possible. This thesis investigates novel techniques for the speech signal generation stage in a speech synthesiser, based on concepts from nonlinear dynamical theory. It focuses on natural–sounding synthesis for voiced speech, coupled with the ability to generate the sound at the required pitch. The one–dimensional voiced speech time–domain signals are embedded into an appropriate higher dimensional space, using Takens’ method of delays. These reconstructed state space representations have approximately the same dynamical properties as the original speech generating system and are thus effective models. A new technique for marking epoch points in voiced speech that operates in the state space domain is proposed. Using the fact that one revolution of the state space representation is equal to one pitch period, pitch synchronous points can be found using a Poincar´e map. Evidently the epoch pulses are pitch synchronous and therefore can be marked. The same state space representation is also used in a locally–linear speech synthesiser. This models the nonlinear dynamics of the speech signal by a series of local approximations, using the original signal as a template. The synthesised speech is natural–sounding because, rather than simply copying the original data, the technique makes use of the local dynamics to create a new, unique signal trajectory. Pitch modification within this synthesis structure is also investigated, with an attempt made to exploit the ˇ Silnikov–type orbit of voiced speech state space reconstructions. However, this technique is found to be incompatible with the locally–linear modelling technique, leaving the pitch modification issue unresolved. A different modelling strategy, using a radial basis function neural network to model the state space dynamics, is then considered. This produces a parametric model of the speech sound. Synthesised speech is obtained by connecting a delayed version of the network output back to the input via a global feedback loop. The network then synthesises speech in a free–running manner. Stability of the output is ensured by using regularisation theory when learning the weights. Complexity is also kept to a minimum because the network centres are fixed on a data–independent hyper–lattice, so only the linear–in–the–parameters weights need to be learnt for each vowel realisation. Pitch modification is again investigated, based around the idea of interpolating the weight vector between different realisations of the same vowel, but at differing pitch values. However modelling the inter–pitch weight vector variations is very difficult, indicating that further study of pitch modification techniques is required before a complete nonlinear synthesiser can be implemented.
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Morales, Santiago Omar Caballero. "Error Modelling Techniques to Improve Automatic Recognition of Dysarthric Speech." Thesis, University of East Anglia, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.514313.
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Zhao, Z. "Integration of neural and stochastic modelling techniques for speech recognition." Thesis, University of Essex, 1992. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.305954.
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Canagarajah, Cedric Nishanthan. "Digital signal processing techniques for speech enhancement in hearing aids." Thesis, University of Cambridge, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.260433.
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Achi, Peter Y. "Speech Enhancement Techniques for Large Space Habitats Using Microphone Arrays." Thesis, University of Louisiana at Lafayette, 2019. http://pqdtopen.proquest.com/#viewpdf?dispub=10813016.
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<p>The astronauts? ability to communicate easily among themselves or with the ship?s computer should be a high priority for the success of missions. Long-duration space habitats--whether spaceships or surface bases--will likely be larger than present-day Earth-to-orbit/Moon transfer ships. Hence an efficient approach would be to free the crew members from the relative burden of having to wear headsets throughout the spacecraft. This can be achieved by placing microphone arrays in all crew-accessible parts of the habitat. Processing algorithms would first localize the speaker and then perform speech enhancement. The background "noise" in a spacecraft is typically fan and duct noise (hum, drone), valve opening/closing (click, hiss), pumps, etc. We simulate such interfering sources by a number of loudspeakers broadcasting various sounds: real ISS sounds, a continuous radio stream, and a poem read by one author. To test the concept, we use a linear 30-microphone array driven by a zero-latency professional audio interface. Speaker localization is obtained by
time-domain processing. To enhance the speech-to-noise ratio, a frequency-domain minimum-variance approach is used.
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Chatlani, Navin. "Advanced signal enhancement techniques with application to speech and hearing." Thesis, University of Strathclyde, 2011. http://oleg.lib.strath.ac.uk:80/R/?func=dbin-jump-full&object_id=23117.
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Advanced signal enhancement techniques with application to speech and hearing are presented that are applied to areas including adaptive noise cancellation (ANC) in noisy speech signals, single channel noise reduction for speech enhancement, voice activity detection (VAD) and noise reduction in binaural hearing aids. The performance enhancement of the new techniques over competing approaches is presented. For the domains of ANC and single channel noise reduction, the use of Empirical Mode Decomposition (EMD) is the underpinning technique employed. A novel approach to dual-channel speech enhancement using Adaptive Empirical Mode Decomposition (SEAEMD) is also presented, when a noise reference is available. The new SEAEMD system incorporates the multi-resolution approach EMD with ANC for effective speech enhancement in stationary and non-stationary noise environments. Two novel Empirical Mode Decomposition based filtering (EMDF) algorithms are presented for single channel speech enhancement. The first system is designed to be particularly effective in low frequency noise environments. The second generalized EMDF system is designed to operate under other noisy conditions, with results presented for babble noise, military vehicle noise and car interior noise. It is shown that the proposed EMDF techniques enhance the speech more effectively than current speech enhancement approaches that use effective noise estimation routines. Speech systems such as hearing aids require fast and computationally inexpensive signal processing technologies. A new and computationally efficient 1-dimensional local binary pattern (1-D LBP) signal processing procedure is designed and applied to (i) signal segmentation and (ii) the VAD problem. Both applications use the underlying features extracted from the 1-D LBP. The simplicity and low computational complexity of 1-D LBP processing are demonstrated. A novel binaural noise reduction system is presented for steering the focus direction of a hearing aid (2 microphones per hearing aid) to additional directions as well as 0/180 degrees. The system places a spatial null in the direction of the target speaker to obtain a noise estimate. The noisy speech signal is then filtered to perform noise reduction, and thus focus on the target speaker located at the desired direction. The results demonstrate its performance at attenuating multiple directional interferers.
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Irvine, James Moir. "Delta modulation techniques for low bit-rate digital speech encoding." Master's thesis, University of Cape Town, 1985. http://hdl.handle.net/11427/7587.
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Includes bibliography.<br>Two new hybrid companding delta modulators for speech encoding are presented here. These modulators differ from the Hybrid Companding Delta Modulator (HCDM) proposed by Un et al in that the two new encoders employ Song Voice Adaptation as the basis of the instantaneous compandor, rather than Constant Factor adaptation. A detailed analysis of the performance, both objective and subjective, of these hybrid codecs has been carried out. Results show that overall the two codecs developed as part of this project are better than the HCDM codec. In addition the new codecs offer simpler implementation in digital hardware than the HCDM. A Computer Aided Test (CAT) system has been developed to simplify the design and test processes for speech codecs.
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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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Gadallah, Mahmoud E. "Data compression techniques for isolated and connected word recognition." Thesis, Cranfield University, 1991. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.280956.
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Ivanuškina, Olga. "Elementy obcojęzyczne w polszczyżnie potocznej młodzieży polskiej (na przykładzie grupy młodzieży z Pogir w rej. wileńskim)." Master's thesis, Lithuanian Academic Libraries Network (LABT), 2006. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2006~D_20060614_125448-20376.
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This paperwork is based on microsociolinguistic research perspective. Speech material was recorded in group of eight young people during nonofficial endurance. The main objective of this paperwork is detail analysis of foreign elements used by Polish youth and presence of their functions in communication process. There were used two research methods: questionnaire and tape-recording of speech during meetings, which topic was religious issue. One part is dedicated to citations (interferences) – elements from foreign languages included into Polish syntax context, which lack any designators of adaptation of grammar and phonetics. In case of classification of citations grammar criteria was accepted as overriding. On this basis all foreign interferences were classified according to parts of speech. The other part of this paperwork presents inputs of longer expressions into speech, which in literature are defined as code switching.
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Ahadi-Sarkani, Seyed Mohammad. "Bayesian and predictive techniques for speaker adaptation." Thesis, University of Cambridge, 1996. https://www.repository.cam.ac.uk/handle/1810/273100.
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Akin, Faith W. "Advanced Techniques in Vestibular Assessment: Tests of Otolith Function." Digital Commons @ East Tennessee State University, 2010. https://dc.etsu.edu/etsu-works/2444.
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Chhatwal, Harprit Singh. "Spectral modelling techniques for speech signals based on linear predictive analysis." Thesis, Imperial College London, 1988. http://hdl.handle.net/10044/1/46996.
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Gouvianakis, Nikolaos. "Speech coding at medium bit rates using analysis by synthesis techniques." Thesis, Loughborough University, 1989. https://dspace.lboro.ac.uk/2134/27741.
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