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Proceedings of the NATO Advanced Study Institute on Computational Models of Speech Pattern Processing, held in St. Helier, Jersey, UK, July 7-18, 1997
Book Synopsis Computational Models of Speech Pattern Processing by : Keith Ponting
Download or read book Computational Models of Speech Pattern Processing written by Keith Ponting and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 478 pages. Available in PDF, EPUB and Kindle. Book excerpt: Proceedings of the NATO Advanced Study Institute on Computational Models of Speech Pattern Processing, held in St. Helier, Jersey, UK, July 7-18, 1997
This book presents a collection of papers from the Spring 1995 Work shop on Computational Approaches to Processing the Prosody of Spon taneous Speech, hosted by the ATR Interpreting Telecommunications Re search Laboratories in Kyoto, Japan. The workshop brought together lead ing researchers in the fields of speech and signal processing, electrical en gineering, psychology, and linguistics, to discuss aspects of spontaneous speech prosody and to suggest approaches to its computational analysis and modelling. The book is divided into four sections. Part I gives an overview and theoretical background to the nature of spontaneous speech, differentiating it from the lab-speech that has been the focus of so many earlier analyses. Part II focuses on the prosodic features of discourse and the structure of the spoken message, Part ilIon the generation and modelling of prosody for computer speech synthesis. Part IV discusses how prosodic information can be used in the context of automatic speech recognition. Each section of the book starts with an invited overview paper to situate the chapters in the context of current research. We feel that this collection of papers offers interesting insights into the scope and nature of the problems concerned with the computational analysis and modelling of real spontaneous speech, and expect that these works will not only form the basis of further developments in each field but also merge to form an integrated computational model of prosody for a better understanding of human processing of the complex interactions of the speech chain.
Book Synopsis Computing PROSODY by : Yoshinori Sagisaka
Download or read book Computing PROSODY written by Yoshinori Sagisaka and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 405 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a collection of papers from the Spring 1995 Work shop on Computational Approaches to Processing the Prosody of Spon taneous Speech, hosted by the ATR Interpreting Telecommunications Re search Laboratories in Kyoto, Japan. The workshop brought together lead ing researchers in the fields of speech and signal processing, electrical en gineering, psychology, and linguistics, to discuss aspects of spontaneous speech prosody and to suggest approaches to its computational analysis and modelling. The book is divided into four sections. Part I gives an overview and theoretical background to the nature of spontaneous speech, differentiating it from the lab-speech that has been the focus of so many earlier analyses. Part II focuses on the prosodic features of discourse and the structure of the spoken message, Part ilIon the generation and modelling of prosody for computer speech synthesis. Part IV discusses how prosodic information can be used in the context of automatic speech recognition. Each section of the book starts with an invited overview paper to situate the chapters in the context of current research. We feel that this collection of papers offers interesting insights into the scope and nature of the problems concerned with the computational analysis and modelling of real spontaneous speech, and expect that these works will not only form the basis of further developments in each field but also merge to form an integrated computational model of prosody for a better understanding of human processing of the complex interactions of the speech chain.
A new perspective on phonetic variation is achieved in this volume through the construction of a series of models of spoken American English. In the past, computer theorists and programmers investigating pronunciation have often relied on their own knowledge of the language or on limited transcription data. Speech recognition researchers, on the other hand, have drawn on a great deal of data but without examining in detail the information about pronunciation the data contains. The authors combine the best of each approach to develop probabilistic and rule-based computational models of transcription data. An ongoing controversy in studies of phonetic variation is the existence and proper definition of a phonetic unit. The authors argue that assumptions about the units of spoken language are critical to a computational model. Their computational models employ suprasegmental elements such as syllable boundaries, stress, and position in a unit called a metrical foot. The use of such elements in modeling data enables the creation of better computational models for both recognition and synthesis technology. This book should be of interest to speech engineers, linguists, and anyone who wishes to understand symbolic systems of communication.
Book Synopsis Computational Models of American Speech by : M. Margaret Withgott
Download or read book Computational Models of American Speech written by M. Margaret Withgott and published by Center for the Study of Language (CSLI). This book was released on 1993 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: A new perspective on phonetic variation is achieved in this volume through the construction of a series of models of spoken American English. In the past, computer theorists and programmers investigating pronunciation have often relied on their own knowledge of the language or on limited transcription data. Speech recognition researchers, on the other hand, have drawn on a great deal of data but without examining in detail the information about pronunciation the data contains. The authors combine the best of each approach to develop probabilistic and rule-based computational models of transcription data. An ongoing controversy in studies of phonetic variation is the existence and proper definition of a phonetic unit. The authors argue that assumptions about the units of spoken language are critical to a computational model. Their computational models employ suprasegmental elements such as syllable boundaries, stress, and position in a unit called a metrical foot. The use of such elements in modeling data enables the creation of better computational models for both recognition and synthesis technology. This book should be of interest to speech engineers, linguists, and anyone who wishes to understand symbolic systems of communication.
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 Dynamic Speech Models by : Li Deng
Download or read book Dynamic Speech Models written by Li Deng and published by Morgan & Claypool Publishers. This book was released on 2006-12-01 with total page 118 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
The interdisciplinary field that deals with the computational modeling of natural language is known as computational linguistics. It studies various computational models that are used to answer linguistic questions. Some of the theoretical frameworks which are used within this field are linguistic production, structural linguistics, linguistic comprehension and developmental linguistics. The discipline makes use of concepts from other fields such as computer science, mathematics, philosophy, psychology, artificial intelligence, cognitive psychology, psycholinguistics, etc. The field helps in the development of speech recognition software. The objective of this book is to give a general view of the different areas of computational linguistics, and its applications. It strives to provide a fair idea about this discipline and to help develop a better understanding of the latest advances within this field. Students, researchers, experts and all associated with speech and language processing will benefit alike from this book.
Book Synopsis Speech and Language Processing: Computational Linguistics and Natural Language Processing by : Elsa Harrington
Download or read book Speech and Language Processing: Computational Linguistics and Natural Language Processing written by Elsa Harrington and published by States Academic Press. This book was released on 2021-11-16 with total page 235 pages. Available in PDF, EPUB and Kindle. Book excerpt: The interdisciplinary field that deals with the computational modeling of natural language is known as computational linguistics. It studies various computational models that are used to answer linguistic questions. Some of the theoretical frameworks which are used within this field are linguistic production, structural linguistics, linguistic comprehension and developmental linguistics. The discipline makes use of concepts from other fields such as computer science, mathematics, philosophy, psychology, artificial intelligence, cognitive psychology, psycholinguistics, etc. The field helps in the development of speech recognition software. The objective of this book is to give a general view of the different areas of computational linguistics, and its applications. It strives to provide a fair idea about this discipline and to help develop a better understanding of the latest advances within this field. Students, researchers, experts and all associated with speech and language processing will benefit alike from this book.
Book Synopsis Speaker Perception and Recognition. An Integrative Framework for Computational Speech Processing by : Oxana Lapteva
Download or read book Speaker Perception and Recognition. An Integrative Framework for Computational Speech Processing written by Oxana Lapteva and published by kassel university press GmbH. This book was released on 2011 with total page 192 pages. Available in PDF, EPUB and Kindle. Book excerpt:
This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human speech and language. It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. C overs the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system integration. Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. Outlines machine learning approaches including static, dynamic and context‐sensitive algorithms for classification and regression. Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus.
Book Synopsis Computational Paralinguistics by : Björn Schuller
Download or read book Computational Paralinguistics written by Björn Schuller and published by John Wiley & Sons. This book was released on 2013-09-17 with total page 330 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the methods, tools and techniques that are currently being used to recognise (automatically) the affect, emotion, personality and everything else beyond linguistics (‘paralinguistics’) expressed by or embedded in human speech and language. It is the first book to provide such a systematic survey of paralinguistics in speech and language processing. The technology described has evolved mainly from automatic speech and speaker recognition and processing, but also takes into account recent developments within speech signal processing, machine intelligence and data mining. Moreover, the book offers a hands-on approach by integrating actual data sets, software, and open-source utilities which will make the book invaluable as a teaching tool and similarly useful for those professionals already in the field. Key features: Provides an integrated presentation of basic research (in phonetics/linguistics and humanities) with state-of-the-art engineering approaches for speech signal processing and machine intelligence. Explains the history and state of the art of all of the sub-fields which contribute to the topic of computational paralinguistics. C overs the signal processing and machine learning aspects of the actual computational modelling of emotion and personality and explains the detection process from corpus collection to feature extraction and from model testing to system integration. Details aspects of real-world system integration including distribution, weakly supervised learning and confidence measures. Outlines machine learning approaches including static, dynamic and context‐sensitive algorithms for classification and regression. Includes a tutorial on freely available toolkits, such as the open-source ‘openEAR’ toolkit for emotion and affect recognition co-developed by one of the authors, and a listing of standard databases and feature sets used in the field to allow for immediate experimentation enabling the reader to build an emotion detection model on an existing corpus.
Human language acquisition has been studied for centuries, but using computational modeling for such studies is a relatively recent trend. However, computational approaches to language learning have become increasingly popular, mainly due to advances in developing machine learning techniques, and the availability of vast collections of experimental data on child language learning and child-adult interaction. Many of the existing computational models attempt to study the complex task of learning a language under cognitive plausibility criteria (such as memory and processing limitations that humans face), and to explain the developmental stages observed in children. By simulating the process of child language learning, computational models can show us which linguistic representations are learnable from the input that children have access to, and which mechanisms yield the same patterns of behaviour that children exhibit during this process. In doing so, computational modeling provides insight into the plausible mechanisms involved in human language acquisition, and inspires the development of better language models and techniques. This book provides an overview of the main research questions in the field of human language acquisition. It reviews the most commonly used computational frameworks, methodologies and resources for modeling child language learning, and the evaluation techniques used for assessing these computational models. The book is aimed at cognitive scientists who want to become familiar with the available computational methods for investigating problems related to human language acquisition, as well as computational linguists who are interested in applying their skills to the study of child language acquisition. Different aspects of language learning are discussed in separate chapters, including the acquisition of the individual words, the general regularities which govern word and sentence form, and the associations between form and meaning. For each of these aspects, the challenges of the task are discussed and the relevant empirical findings on children are summarized. Furthermore, the existing computational models that attempt to simulate the task under study are reviewed, and a number of case studies are presented. Table of Contents: Overview / Computational Models of Language Learning / Learning Words / Putting Words Together / Form--Meaning Associations / Final Thoughts
Book Synopsis Computational Modeling of Human Language Acquisition by : Afra Alishahi
Download or read book Computational Modeling of Human Language Acquisition written by Afra Alishahi and published by Springer Nature. This book was released on 2022-06-01 with total page 94 pages. Available in PDF, EPUB and Kindle. Book excerpt: Human language acquisition has been studied for centuries, but using computational modeling for such studies is a relatively recent trend. However, computational approaches to language learning have become increasingly popular, mainly due to advances in developing machine learning techniques, and the availability of vast collections of experimental data on child language learning and child-adult interaction. Many of the existing computational models attempt to study the complex task of learning a language under cognitive plausibility criteria (such as memory and processing limitations that humans face), and to explain the developmental stages observed in children. By simulating the process of child language learning, computational models can show us which linguistic representations are learnable from the input that children have access to, and which mechanisms yield the same patterns of behaviour that children exhibit during this process. In doing so, computational modeling provides insight into the plausible mechanisms involved in human language acquisition, and inspires the development of better language models and techniques. This book provides an overview of the main research questions in the field of human language acquisition. It reviews the most commonly used computational frameworks, methodologies and resources for modeling child language learning, and the evaluation techniques used for assessing these computational models. The book is aimed at cognitive scientists who want to become familiar with the available computational methods for investigating problems related to human language acquisition, as well as computational linguists who are interested in applying their skills to the study of child language acquisition. Different aspects of language learning are discussed in separate chapters, including the acquisition of the individual words, the general regularities which govern word and sentence form, and the associations between form and meaning. For each of these aspects, the challenges of the task are discussed and the relevant empirical findings on children are summarized. Furthermore, the existing computational models that attempt to simulate the task under study are reviewed, and a number of case studies are presented. Table of Contents: Overview / Computational Models of Language Learning / Learning Words / Putting Words Together / Form--Meaning Associations / Final Thoughts
It is with great pleasure that I present this third volume of the series "Advanced Applications in Pattern Recognition." It represents the summary of many man- (and woman-) years of effort in the field of speech recognition by tne author's former team at the University of Turin. It combines the best results in fuzzy-set theory and artificial intelligence to point the way to definitive solutions to the speech-recognition problem. It is my hope that it will become a classic work in this field. I take this opportunity to extend my thanks and appreciation to Sy Marchand, Plenum's Senior Editor responsible for overseeing this series, and to Susan Lee and Jo Winton, who had the monumental task of preparing the camera-ready master sheets for publication. Morton Nadler General Editor vii PREFACE Si parva licet componere magnis Virgil, Georgics, 4,176 (37-30 B.C.) The work reported in this book results from years of research oriented toward the goal of making an experimental model capable of understanding spoken sentences of a natural language. This is, of course, a modest attempt compared to the complexity of the functions performed by the human brain. A method is introduced for conce1v1ng modules performing perceptual tasks and for combining them in a speech understanding system.
Book Synopsis Computer Models of Speech Using Fuzzy Algorithms by : Renato de Mori
Download or read book Computer Models of Speech Using Fuzzy Algorithms written by Renato de Mori and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 505 pages. Available in PDF, EPUB and Kindle. Book excerpt: It is with great pleasure that I present this third volume of the series "Advanced Applications in Pattern Recognition." It represents the summary of many man- (and woman-) years of effort in the field of speech recognition by tne author's former team at the University of Turin. It combines the best results in fuzzy-set theory and artificial intelligence to point the way to definitive solutions to the speech-recognition problem. It is my hope that it will become a classic work in this field. I take this opportunity to extend my thanks and appreciation to Sy Marchand, Plenum's Senior Editor responsible for overseeing this series, and to Susan Lee and Jo Winton, who had the monumental task of preparing the camera-ready master sheets for publication. Morton Nadler General Editor vii PREFACE Si parva licet componere magnis Virgil, Georgics, 4,176 (37-30 B.C.) The work reported in this book results from years of research oriented toward the goal of making an experimental model capable of understanding spoken sentences of a natural language. This is, of course, a modest attempt compared to the complexity of the functions performed by the human brain. A method is introduced for conce1v1ng modules performing perceptual tasks and for combining them in a speech understanding system.
Book Synopsis Speech & Language Processing by : Dan Jurafsky
Download or read book Speech & Language Processing written by Dan Jurafsky and published by Pearson Education India. This book was released on 2000-09 with total page 912 pages. Available in PDF, EPUB and Kindle. Book excerpt:
