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Feature Based Pronunciation Modeling For Automatic Speech Recognition
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Book Synopsis Statistical Pronunciation Modeling for Non-Native Speech Processing by : Rainer E. Gruhn
Download or read book Statistical Pronunciation Modeling for Non-Native Speech Processing written by Rainer E. Gruhn and published by Springer Science & Business Media. This book was released on 2011-05-08 with total page 118 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this work, the authors present a fully statistical approach to model non--native speakers' pronunciation. Second-language speakers pronounce words in multiple different ways compared to the native speakers. Those deviations, may it be phoneme substitutions, deletions or insertions, can be modelled automatically with the new method presented here. The methods is based on a discrete hidden Markov model as a word pronunciation model, initialized on a standard pronunciation dictionary. The implementation and functionality of the methodology has been proven and verified with a test set of non-native English in the regarding accent. The book is written for researchers with a professional interest in phonetics and automatic speech and speaker recognition.
Book Synopsis The Application of Hidden Markov Models in Speech Recognition by : Mark Gales
Download or read book The Application of Hidden Markov Models in Speech Recognition written by Mark Gales and published by Now Publishers Inc. This book was released on 2008 with total page 125 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Application of Hidden Markov Models in Speech Recognition presents the core architecture of a HMM-based LVCSR system and proceeds to describe the various refinements which are needed to achieve state-of-the-art performance.
Book Synopsis Speaker Classification I by : Christian Müller
Download or read book Speaker Classification I written by Christian Müller and published by Springer. This book was released on 2007-08-28 with total page 363 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume and its companion volume LNAI 4441 constitute a state-of-the-art survey in the field of speaker classification. Together they address such intriguing issues as how speaker characteristics are manifested in voice and speaking behavior. The nineteen contributions in this volume are organized into topical sections covering fundamentals, characteristics, applications, methods, and evaluation.
Book Synopsis Spoken Language Systems by : Seiichi Nakagawa
Download or read book Spoken Language Systems written by Seiichi Nakagawa and published by IOS Press. This book was released on 2005 with total page 368 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech processing research in Japan started in the 1940s. This book provides a compendium of the prominent studies on spoken language systems developed in Japan. It offers a comprehensive introduction to the major works conducted at Japanese research institutes that are developing spoken language systems.
Book Synopsis Robust Automatic Speech Recognition by : Jinyu Li
Download or read book Robust Automatic Speech Recognition written by Jinyu Li and published by Academic Press. This book was released on 2015-10-30 with total page 308 pages. Available in PDF, EPUB and Kindle. Book excerpt: Robust Automatic Speech Recognition: A Bridge to Practical Applications establishes a solid foundation for automatic speech recognition that is robust against acoustic environmental distortion. It provides a thorough overview of classical and modern noise-and reverberation robust techniques that have been developed over the past thirty years, with an emphasis on practical methods that have been proven to be successful and which are likely to be further developed for future applications.The strengths and weaknesses of robustness-enhancing speech recognition techniques are carefully analyzed. The book covers noise-robust techniques designed for acoustic models which are based on both Gaussian mixture models and deep neural networks. In addition, a guide to selecting the best methods for practical applications is provided.The reader will: - Gain a unified, deep and systematic understanding of the state-of-the-art technologies for robust speech recognition - Learn the links and relationship between alternative technologies for robust speech recognition - Be able to use the technology analysis and categorization detailed in the book to guide future technology development - Be able to develop new noise-robust methods in the current era of deep learning for acoustic modeling in speech recognition - The first book that provides a comprehensive review on noise and reverberation robust speech recognition methods in the era of deep neural networks - Connects robust speech recognition techniques to machine learning paradigms with rigorous mathematical treatment - Provides elegant and structural ways to categorize and analyze noise-robust speech recognition techniques - Written by leading researchers who have been actively working on the subject matter in both industrial and academic organizations for many years
Book Synopsis Automatic Speech and Speaker Recognition by : Joseph Keshet
Download or read book Automatic Speech and Speaker Recognition written by Joseph Keshet and published by John Wiley & Sons. This book was released on 2009-04-27 with total page 268 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book discusses large margin and kernel methods for speech and speaker recognition Speech and Speaker Recognition: Large Margin and Kernel Methods is a collation of research in the recent advances in large margin and kernel methods, as applied to the field of speech and speaker recognition. It presents theoretical and practical foundations of these methods, from support vector machines to large margin methods for structured learning. It also provides examples of large margin based acoustic modelling for continuous speech recognizers, where the grounds for practical large margin sequence learning are set. Large margin methods for discriminative language modelling and text independent speaker verification are also addressed in this book. Key Features: Provides an up-to-date snapshot of the current state of research in this field Covers important aspects of extending the binary support vector machine to speech and speaker recognition applications Discusses large margin and kernel method algorithms for sequence prediction required for acoustic modeling Reviews past and present work on discriminative training of language models, and describes different large margin algorithms for the application of part-of-speech tagging Surveys recent work on the use of kernel approaches to text-independent speaker verification, and introduces the main concepts and algorithms Surveys recent work on kernel approaches to learning a similarity matrix from data This book will be of interest to researchers, practitioners, engineers, and scientists in speech processing and machine learning fields.
Book Synopsis Language Modeling for Automatic Speech Recognition of Inflective Languages by : Gregor Donaj
Download or read book Language Modeling for Automatic Speech Recognition of Inflective Languages written by Gregor Donaj and published by Springer. This book was released on 2016-08-29 with total page 77 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers language modeling and automatic speech recognition for inflective languages (e.g. Slavic languages), which represent roughly half of the languages spoken in Europe. These languages do not perform as well as English in speech recognition systems and it is therefore harder to develop an application with sufficient quality for the end user. The authors describe the most important language features for the development of a speech recognition system. This is then presented through the analysis of errors in the system and the development of language models and their inclusion in speech recognition systems, which specifically address the errors that are relevant for targeted applications. The error analysis is done with regard to morphological characteristics of the word in the recognized sentences. The book is oriented towards speech recognition with large vocabularies and continuous and even spontaneous speech. Today such applications work with a rather small number of languages compared to the number of spoken languages.
Book Synopsis Multilingual Speech Processing by : Tanja Schultz
Download or read book Multilingual Speech Processing written by Tanja Schultz and published by Elsevier. This book was released on 2006-06-12 with total page 540 pages. Available in PDF, EPUB and Kindle. Book excerpt: Tanja Schultz and Katrin Kirchhoff have compiled a comprehensive overview of speech processing from a multilingual perspective. By taking this all-inclusive approach to speech processing, the editors have included theories, algorithms, and techniques that are required to support spoken input and output in a large variety of languages. Multilingual Speech Processing presents a comprehensive introduction to research problems and solutions, both from a theoretical as well as a practical perspective, and highlights technology that incorporates the increasing necessity for multilingual applications in our global community. Current challenges of speech processing and the feasibility of sharing data and system components across different languages guide contributors in their discussions of trends, prognoses and open research issues. This includes automatic speech recognition and speech synthesis, but also speech-to-speech translation, dialog systems, automatic language identification, and handling non-native speech. The book is complemented by an overview of multilingual resources, important research trends, and actual speech processing systems that are being deployed in multilingual human-human and human-machine interfaces. Researchers and developers in industry and academia with different backgrounds but a common interest in multilingual speech processing will find an excellent overview of research problems and solutions detailed from theoretical and practical perspectives. - State-of-the-art research with a global perspective by authors from the USA, Asia, Europe, and South Africa - The only comprehensive introduction to multilingual speech processing currently available - Detailed presentation of technological advances integral to security, financial, cellular and commercial applications
Book Synopsis Automatic Speech and Speaker Recognition by : Chin-Hui Lee
Download or read book Automatic Speech and Speaker Recognition written by Chin-Hui Lee and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 524 pages. Available in PDF, EPUB and Kindle. Book excerpt: Research in the field of automatic speech and speaker recognition has made a number of significant advances in the last two decades, influenced by advances in signal processing, algorithms, architectures, and hardware. These advances include: the adoption of a statistical pattern recognition paradigm; the use of the hidden Markov modeling framework to characterize both the spectral and the temporal variations in the speech signal; the use of a large set of speech utterance examples from a large population of speakers to train the hidden Markov models of some fundamental speech units; the organization of speech and language knowledge sources into a structural finite state network; and the use of dynamic, programming based heuristic search methods to find the best word sequence in the lexical network corresponding to the spoken utterance. Automatic Speech and Speaker Recognition: Advanced Topics groups together in a single volume a number of important topics on speech and speaker recognition, topics which are of fundamental importance, but not yet covered in detail in existing textbooks. Although no explicit partition is given, the book is divided into five parts: Chapters 1-2 are devoted to technology overviews; Chapters 3-12 discuss acoustic modeling of fundamental speech units and lexical modeling of words and pronunciations; Chapters 13-15 address the issues related to flexibility and robustness; Chapter 16-18 concern the theoretical and practical issues of search; Chapters 19-20 give two examples of algorithm and implementational aspects for recognition system realization. Audience: A reference book for speech researchers and graduate students interested in pursuing potential research on the topic. May also be used as a text for advanced courses on the subject.
Book Synopsis Dynamic Pronunciation Models for Automatic Speech Recognition by : Eric Fosler-Lussier
Download or read book Dynamic Pronunciation Models for Automatic Speech Recognition written by Eric Fosler-Lussier and published by . This book was released on 1999 with total page 498 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Spoken Dialogue Systems for Ambient Environments by : Gary Geunbae Lee
Download or read book Spoken Dialogue Systems for Ambient Environments written by Gary Geunbae Lee and published by Springer Science & Business Media. This book was released on 2010-09-27 with total page 209 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the refereed proceedings of the Second International Workshop on Spoken Dialogue Systems, IWDS 2010, held in Gotemba, Japan, in October 2010. The 22 session papers presented together with 2 invited keynote talks were carefully reviewed and selected from numerous submissions. The papers deal with topics around Spoken Dialogue Systems for Ambient Environment and discuss common issues of theories, applications, evaluation, limitations, general tools and techniques.
Book Synopsis Advances in Speech Recognition by : Noam Shabtai
Download or read book Advances in Speech Recognition written by Noam Shabtai and published by BoD – Books on Demand. This book was released on 2010-08-16 with total page 177 pages. Available in PDF, EPUB and Kindle. Book excerpt: In the last decade, further applications of speech processing were developed, such as speaker recognition, human-machine interaction, non-English speech recognition, and non-native English speech recognition. This book addresses a few of these applications. Furthermore, major challenges that were typically ignored in previous speech recognition research, such as noise and reverberation, appear repeatedly in recent papers. I would like to sincerely thank the contributing authors, for their effort to bring their insights and perspectives on current open questions in speech recognition research.
Book Synopsis Automatic Assessment of Children Speech to Support Language Learning by : Christian Hacker
Download or read book Automatic Assessment of Children Speech to Support Language Learning written by Christian Hacker and published by Logos Verlag Berlin GmbH. This book was released on 2009 with total page 272 pages. Available in PDF, EPUB and Kindle. Book excerpt: Focus of this work are pattern recognition related aspects of computer assisted pronunciation training (CAPT) for second language learning. An overview of commercial systems shows that pronunciation training is being addressed by the growing field of computer assisted language learning only to a small extend, although in the state-of-the-art section a number of such approaches for automatic assessment can already be presented. In the present thesis different approaches are extended and combined. In particular a large set of nearly 200 pronunciation and prosodic features is developed. By this approach pronunciation scoring is regarded as classification task in high-dimensional feature space. Automatic speech recognition is the basis of most pronunciation scoring algorithms. In this thesis a system is presented, which supports second language learning at school, i.e. the target users are children. For this reason a state-of-the-art speech recognition engine is adapted to children speech, since young speakers are only hardly recognised by automatic systems. Phonetically motivated rules for typical mispronunciation errors are integrated into the system to make it suitable for pronunciation scoring. Evaluating an algorithm for pronunciation assessment is more difficult than simply counting the correctly recognised mistakes, since there exists no objective ground truth. This can be shown by evaluating the annotations of 14 teachers. However, with different measures it can be verified that the accuracy of the system (in comparison with teachers) thoroughly reaches the agreement among teachers. The evaluation is conducted with native German speakers learning English.
Book Synopsis Lexicon Development for Speech and Language Processing by : Frank Van Eynde
Download or read book Lexicon Development for Speech and Language Processing written by Frank Van Eynde and published by Springer. This book was released on 2014-11-14 with total page 302 pages. Available in PDF, EPUB and Kindle. Book excerpt: This work offers a survey of methods and techniques for structuring, acquiring and maintaining lexical resources for speech and language processing. The first chapter provides a broad survey of the field of computational lexicography, introducing most of the issues, terms and topics which are addressed in more detail in the rest of the book. The next two chapters focus on the structure and the content of man-made lexicons, concentrating respectively on (morpho- )syntactic and (morpho- )phonological information. Both chapters adopt a declarative constraint-based methodology and pay ample attention to the various ways in which lexical generalizations can be formalized and exploited to enhance the consistency and to reduce the redundancy of lexicons. A complementary perspective is offered in the next two chapters, which present techniques for automatically deriving lexical resources from text corpora. These chapters adopt an inductive data-oriented methodology and focus also on methods for tokenization, lemmatization and shallow parsing. The next three chapters focus on speech synthesis and speech recognition.
Download or read book Dynamic Speech Models written by Li Deng and published by Springer Nature. This book was released on 2022-05-31 with total page 105 pages. Available in PDF, EPUB and Kindle. Book excerpt: Speech dynamics refer to the temporal characteristics in all stages of the human speech communication process. This speech “chain” starts with the formation of a linguistic message in a speaker's brain and ends with the arrival of the message in a listener's brain. Given the intricacy of the dynamic speech process and its fundamental importance in human communication, this monograph is intended to provide a comprehensive material on mathematical models of speech dynamics and to address the following issues: How do we make sense of the complex speech process in terms of its functional role of speech communication? How do we quantify the special role of speech timing? How do the dynamics relate to the variability of speech that has often been said to seriously hamper automatic speech recognition? How do we put the dynamic process of speech into a quantitative form to enable detailed analyses? And finally, how can we incorporate the knowledge of speech dynamics into computerized speech analysis and recognition algorithms? The answers to all these questions require building and applying computational models for the dynamic speech process. What are the compelling reasons for carrying out dynamic speech modeling? We provide the answer in two related aspects. First, scientific inquiry into the human speech code has been relentlessly pursued for several decades. As an essential carrier of human intelligence and knowledge, speech is the most natural form of human communication. Embedded in the speech code are linguistic (as well as para-linguistic) messages, which are conveyed through four levels of the speech chain. Underlying the robust encoding and transmission of the linguistic messages are the speech dynamics at all the four levels. Mathematical modeling of speech dynamics provides an effective tool in the scientific methods of studying the speech chain. Such scientific studies help understand why humans speak as they do and how humans exploit redundancy and variability by way of multitiered dynamic processes to enhance the efficiency and effectiveness of human speech communication. Second, advancement of human language technology, especially that in automatic recognition of natural-style human speech is also expected to benefit from comprehensive computational modeling of speech dynamics. The limitations of current speech recognition technology are serious and are well known. A commonly acknowledged and frequently discussed weakness of the statistical model underlying current speech recognition technology is the lack of adequate dynamic modeling schemes to provide correlation structure across the temporal speech observation sequence. Unfortunately, due to a variety of reasons, the majority of current research activities in this area favor only incremental modifications and improvements to the existing HMM-based state-of-the-art. For example, while the dynamic and correlation modeling is known to be an important topic, most of the systems nevertheless employ only an ultra-weak form of speech dynamics; e.g., differential or delta parameters. Strong-form dynamic speech modeling, which is the focus of this monograph, may serve as an ultimate solution to this problem. After the introduction chapter, the main body of this monograph consists of four chapters. They cover various aspects of theory, algorithms, and applications of dynamic speech models, and provide a comprehensive survey of the research work in this area spanning over past 20~years. This monograph is intended as advanced materials of speech and signal processing for graudate-level teaching, for professionals and engineering practioners, as well as for seasoned researchers and engineers specialized in speech processing
Book Synopsis Incorporating Knowledge Sources into Statistical Speech Recognition by : Sakriani Sakti
Download or read book Incorporating Knowledge Sources into Statistical Speech Recognition written by Sakriani Sakti and published by Springer Science & Business Media. This book was released on 2009-02-27 with total page 207 pages. Available in PDF, EPUB and Kindle. Book excerpt: Incorporating Knowledge Sources into Statistical Speech Recognition addresses the problem of developing efficient automatic speech recognition (ASR) systems, which maintain a balance between utilizing a wide knowledge of speech variability, while keeping the training / recognition effort feasible and improving speech recognition performance. The book provides an efficient general framework to incorporate additional knowledge sources into state-of-the-art statistical ASR systems. It can be applied to many existing ASR problems with their respective model-based likelihood functions in flexible ways.
Book Synopsis Automatic Speech Recognition by : Dong Yu
Download or read book Automatic Speech Recognition written by Dong Yu and published by Springer. This book was released on 2014-11-11 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive overview of the recent advancement in the field of automatic speech recognition with a focus on deep learning models including deep neural networks and many of their variants. This is the first automatic speech recognition book dedicated to the deep learning approach. In addition to the rigorous mathematical treatment of the subject, the book also presents insights and theoretical foundation of a series of highly successful deep learning models.
