Reinforcement Learning Methods In Speech And Language Technology
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Reinforcement Learning Methods In Speech And Language Technology
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Author : Baihan Lin
language : en
Publisher: Springer Nature
Release Date : 2024-11-11
Reinforcement Learning Methods In Speech And Language Technology written by Baihan Lin and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-11 with Technology & Engineering categories.
This book offers a comprehensive guide to reinforcement learning (RL) and bandits methods, specifically tailored for advancements in speech and language technology. Starting with a foundational overview of RL and bandit methods, the book dives into their practical applications across a wide array of speech and language tasks. Readers will gain insights into how these methods shape solutions in automatic speech recognition (ASR), speaker recognition, diarization, spoken and natural language understanding (SLU/NLU), text-to-speech (TTS) synthesis, natural language generation (NLG), and conversational recommendation systems (CRS). Further, the book delves into cutting-edge developments in large language models (LLMs) and discusses the latest strategies in RL, highlighting the emerging fields of multi-agent systems and transfer learning. Emphasizing real-world applications, the book provides clear, step-by-step guidance on employing RL and bandit methods to address challenges in speech and language technology. It includes case studies and practical tips that equip readers to apply these methods to their own projects. As a timely and crucial resource, this book is ideal for speech and language researchers, engineers, students, and practitioners eager to enhance the performance of speech and language systems and to innovate with new interactive learning paradigms from an interface design perspective.
Speech And Language Processing
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Author : Daniel Jurafsky
language : en
Publisher:
Release Date : 2000-01
Speech And Language Processing written by Daniel Jurafsky and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000-01 with Automatic speech recognition categories.
This book takes an empirical approach to language processing, based on applying statistical and other machine-learning algorithms to large corpora.Methodology boxes are included in each chapter. Each chapter is built around one or more worked examples to demonstrate the main idea of the chapter. Covers the fundamental algorithms of various fields, whether originally proposed for spoken or written language to demonstrate how the same algorithm can be used for speech recognition and word-sense disambiguation. Emphasis on web and other practical applications. Emphasis on scientific evaluation. Useful as a reference for professionals in any of the areas of speech and language processing.
Reinforcement Learning
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Author : Richard S. Sutton
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06
Reinforcement Learning written by Richard S. Sutton and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Computers categories.
Reinforcement learning is the learning of a mapping from situations to actions so as to maximize a scalar reward or reinforcement signal. The learner is not told which action to take, as in most forms of machine learning, but instead must discover which actions yield the highest reward by trying them. In the most interesting and challenging cases, actions may affect not only the immediate reward, but also the next situation, and through that all subsequent rewards. These two characteristics -- trial-and-error search and delayed reward -- are the most important distinguishing features of reinforcement learning. Reinforcement learning is both a new and a very old topic in AI. The term appears to have been coined by Minsk (1961), and independently in control theory by Walz and Fu (1965). The earliest machine learning research now viewed as directly relevant was Samuel's (1959) checker player, which used temporal-difference learning to manage delayed reward much as it is used today. Of course learning and reinforcement have been studied in psychology for almost a century, and that work has had a very strong impact on the AI/engineering work. One could in fact consider all of reinforcement learning to be simply the reverse engineering of certain psychological learning processes (e.g. operant conditioning and secondary reinforcement). Reinforcement Learning is an edited volume of original research, comprising seven invited contributions by leading researchers.
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques
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Author : Olivas, Emilio Soria
language : en
Publisher: IGI Global
Release Date : 2009-08-31
Handbook Of Research On Machine Learning Applications And Trends Algorithms Methods And Techniques written by Olivas, Emilio Soria and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-08-31 with Computers categories.
"This book investiges machine learning (ML), one of the most fruitful fields of current research, both in the proposal of new techniques and theoretic algorithms and in their application to real-life problems"--Provided by publisher.
Automatic Speech Recognition
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Author : Dong Yu
language : en
Publisher: Springer
Release Date : 2014-11-11
Automatic Speech Recognition written by Dong Yu and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-11-11 with Technology & Engineering categories.
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.
Data Driven Methods For Adaptive Spoken Dialogue Systems
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Author : Oliver Lemon
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-20
Data Driven Methods For Adaptive Spoken Dialogue Systems written by Oliver Lemon and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-20 with Computers categories.
Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
New Language Technologies And Linguistic Research
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Author : Sandra Maria Aluisio
language : en
Publisher: Cambridge Scholars Publishing
Release Date : 2014-03-25
New Language Technologies And Linguistic Research written by Sandra Maria Aluisio and has been published by Cambridge Scholars Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-03-25 with Computers categories.
This book is a collection of the papers presented and discussed at the 11th Corpus Linguistics Symposium (ELC 2012), held at the Instituto de Ciências Matemáticas e de Computação (Institute of Mathematics and Computer Science) of the University of São Paulo, at São Carlos, Brazil. The sessions addressed the following six topics: Corpus Linguistics and Language Description; Translation, Terminology and Corpora; Spoken Language and Corpora; Natural Language Processing and Corpora; Corpus Annotation; and Corpora and Multiple Documents. These unique studies will inspire readers with an interest in Linguistics, and will provide motivation for conducting further research in the interdisciplinary area of Language Technologies and Linguistic Research.
Data Driven Methods For Adaptive Spoken Dialogue Systems
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Author : Oliver Lemon
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-10-21
Data Driven Methods For Adaptive Spoken Dialogue Systems written by Oliver Lemon and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-10-21 with Computers categories.
Data driven methods have long been used in Automatic Speech Recognition (ASR) and Text-To-Speech (TTS) synthesis and have more recently been introduced for dialogue management, spoken language understanding, and Natural Language Generation. Machine learning is now present “end-to-end” in Spoken Dialogue Systems (SDS). However, these techniques require data collection and annotation campaigns, which can be time-consuming and expensive, as well as dataset expansion by simulation. In this book, we provide an overview of the current state of the field and of recent advances, with a specific focus on adaptivity.
Proceedings Of 5th International Conference On Recent Trends In Machine Learning Iot Smart Cities And Applications
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Author : Vinit Kumar Gunjan
language : en
Publisher: Springer Nature
Release Date : 2025-02-27
Proceedings Of 5th International Conference On Recent Trends In Machine Learning Iot Smart Cities And Applications written by Vinit Kumar Gunjan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-27 with Technology & Engineering categories.
This book contains original, peer-reviewed research articles from the 5th International Conference on Recent Trends in Machine Learning, IoT, Smart Cities, and Applications, held in Hyderabad, India on 28–29 March 2024. It includes the most recent research trends and advancements in machine learning, smart cities, IoT, AI, cyber-physical systems, cybernetics, data science, neural networks, and cognition. This book addresses the comprehensive nature of AI, ML, and DL to highlight its role in the modelling, identification, optimisation, prediction, forecasting, and control of future intelligent systems.
Human Centric Interfaces For Ambient Intelligence
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Author : Hamid Aghajan
language : en
Publisher: Academic Press
Release Date : 2009-09-25
Human Centric Interfaces For Ambient Intelligence written by Hamid Aghajan and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-09-25 with Computers categories.
To create truly effective human-centric ambient intelligence systems both engineering and computing methods are needed. This is the first book to bridge data processing and intelligent reasoning methods for the creation of human-centered ambient intelligence systems. Interdisciplinary in nature, the book covers topics such as multi-modal interfaces, human-computer interaction, smart environments and pervasive computing, addressing principles, paradigms, methods and applications. This book will be an ideal reference for university researchers, R&D engineers, computer engineers, and graduate students working in signal, speech and video processing, multi-modal interfaces, human-computer interaction and applications of ambient intelligence. Hamid Aghajan is a Professor of Electrical Engineering (consulting) at Stanford University, USA. His research is on user-centric vision applications in smart homes, assisted living / well being, smart meetings, and avatar-based social interactions. He is Editor-in-Chief of "Journal of Ambient Intelligence and Smart Environments", has chaired ACM/IEEE ICDSC 2008, and organized workshops/sessions/tutorials at ECCV, ACM MM, FG, ECAI, ICASSP, CVPR. Juan Carlos Augusto is a Lecturer at the University of Ulster, UK. He is conducting research on Smart Homes and Classrooms. He has given tutorials at IJCAI'07 and AAAI'08. He is Editor-in-Chief of the Book Series on "Ambient Intelligence and Smart Environments" and the "Journal of Ambient Intelligence and Smart Environments". He has co-Chaired ICOST'06, AITAmI'06/07/08, and is Workshops Chair for IE'09. Ramón López-Cózar Delgado is a Professor at the Faculty of Computer Science and Telecommunications of the University of Granada, Spain. His research interests include speech recognition and understanding, dialogue management and Ambient Intelligence. He is a member of ISCA (International Speech Communication Association), SEPLN (Spanish Society on Natural Language Processing) and AIPO (Spanish Society on HCI). - Integrates engineering and computing methods that are essential for designing and implementing highly effective ambient intelligence systems - Contains contributions from the world's leading experts in academia and industry - Gives a complete overview of the principles, paradigms and applications of human-centric ambient intelligence systems