Fundamentals of Speaker Recognition

Author: Homayoon Beigi
Publisher: Springer Science & Business Media
ISBN: 0387775927
Format: PDF, Docs
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An emerging technology, Speaker Recognition is becoming well-known for providing voice authentication over the telephone for helpdesks, call centres and other enterprise businesses for business process automation. "Fundamentals of Speaker Recognition" introduces Speaker Identification, Speaker Verification, Speaker (Audio Event) Classification, Speaker Detection, Speaker Tracking and more. The technical problems are rigorously defined, and a complete picture is made of the relevance of the discussed algorithms and their usage in building a comprehensive Speaker Recognition System. Designed as a textbook with examples and exercises at the end of each chapter, "Fundamentals of Speaker Recognition" is suitable for advanced-level students in computer science and engineering, concentrating on biometrics, speech recognition, pattern recognition, signal processing and, specifically, speaker recognition. It is also a valuable reference for developers of commercial technology and for speech scientists. Please click on the link under "Additional Information" to view supplemental information including the Table of Contents and Index.

Fundamentals of Speaker Recognition

Author: Homayoon Beigi
Publisher: Springer
ISBN: 9781489979223
Format: PDF, Kindle
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Speaker Recognition is a popular new technology that can authenticate voices over the phone. This comprehensive text covers the basics and the latest developments of this technology and includes examples and exercises at the end of each chapter.

Robust Speaker Recognition in Noisy Environments

Author: K. Sreenivasa Rao
Publisher: Springer
ISBN: 3319071300
Format: PDF, ePub, Docs
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This book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models.

Robust Automatic Speech Recognition

Author: Jinyu Li
Publisher: Academic Press
ISBN: 0128026162
Format: PDF, Mobi
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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

Fundamentals of Speech Recognition

Author: Lawrence R. Rabiner
Publisher: Prentice Hall
ISBN: 9780130151575
Format: PDF, Mobi
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Provides a theoretically sound, technically accurate, and complete description of the basic knowledge and ideas that constitute a modern system for speech recognition by machine. Covers production, perception, and acoustic-phonetic characterization of the speech signal; signal processing and analysis methods for speech recognition; pattern comparison techniques; speech recognition system design and implementation; theory and implementation of hidden Markov models; speech recognition based on connected word models; large vocabulary continuous speech recognition; and task- oriented application of automatic speech recognition. For practicing engineers, scientists, linguists, and programmers interested in speech recognition.

Statistical Methods for Speech Recognition

Author: Frederick Jelinek
Publisher: MIT Press
ISBN: 9780262100663
Format: PDF
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This book reflects decades of important research on the mathematical foundations of speech recognition. It focuses on underlying statistical techniques such as hidden Markov models, decision trees, the expectation-maximization algorithm, information theoretic goodness criteria, maximum entropy probability estimation, parameter and data clustering, and smoothing of probability distributions. The author's goal is to present these principles clearly in the simplest setting, to show the advantages of self-organization from real data, and to enable the reader to apply the techniques.

Speaker Classification I

Author: Christian Müller
Publisher: Springer
ISBN: 354074200X
Format: PDF, Docs
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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.

SPEECH RECOGNITION THEORY AND C IMPLEMENTATION With CD

Author: Claudio Becchetti
Publisher: John Wiley & Sons
ISBN: 9788126517749
Format: PDF
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Special Features: · Source codes for compiling and implementing ASR algorithms in C++ are included in electronic format on an accompanying CD-ROM· Contains a practical account of the functioning of ASR· Includes implementation-oriented mathematical and technical explanations of ASR· Features a stage-by-stage explanation of how to create an ASR interface· Can be used both for teaching speech recognition techniques and testing and development of new systems on digital signal processing hardware About The Book: Automatic Speech Recognition (ASR) is becoming increasingly prevalent in such applications as private telephone exchanges and real-time on-line telephone information services. This book introduces the principles of ASR systems, including the theory and the implementation issues behind multi-speaker continuous speech ASR. The book supplies the full C++ code to further clarify the implementation details of a typical commercial/laboratory ASR system and to allow the readers to reach practical solutions for ASR-related problems.About the topic/technology Automatic Speech Recognition (ASR) is the technology behind the voice-triggered computer menus. Uses of these systems are now proliferating rapidly and include private telephone exchanges and real-time on-line telephone information services.

Robust Speech Recognition of Uncertain or Missing Data

Author: Dorothea Kolossa
Publisher: Springer Science & Business Media
ISBN: 9783642213175
Format: PDF, ePub, Mobi
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Automatic speech recognition suffers from a lack of robustness with respect to noise, reverberation and interfering speech. The growing field of speech recognition in the presence of missing or uncertain input data seeks to ameliorate those problems by using not only a preprocessed speech signal but also an estimate of its reliability to selectively focus on those segments and features that are most reliable for recognition. This book presents the state of the art in recognition in the presence of uncertainty, offering examples that utilize uncertainty information for noise robustness, reverberation robustness, simultaneous recognition of multiple speech signals, and audiovisual speech recognition. The book is appropriate for scientists and researchers in the field of speech recognition who will find an overview of the state of the art in robust speech recognition, professionals working in speech recognition who will find strategies for improving recognition results in various conditions of mismatch, and lecturers of advanced courses on speech processing or speech recognition who will find a reference and a comprehensive introduction to the field. The book assumes an understanding of the fundamentals of speech recognition using Hidden Markov Models.

Fundamentals of speech synthesis and speech recognition

Author: Éric Keller
Publisher: John Wiley & Sons Inc
ISBN:
Format: PDF, Docs
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Explains and discusses how human speakers and listeners process speech and language. Focuses on those elements of current research which have the most bearing on future developments in the production of truly natural-sounding speech and the reliable recognition of continuous speech. Presents a concise and clear introduction to this increasingly complex and interdisciplinary field.