Speech Signal Processing Based On Deep Learning In Complex Acoustic Environments

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Speech Signal Processing Based On Deep Learning In Complex Acoustic Environments

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Author : Xiao-Lei Zhang
language : en
Publisher: Elsevier
Release Date : 2024-09-04

Speech Signal Processing Based On Deep Learning In Complex Acoustic Environments written by Xiao-Lei Zhang and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-04 with Computers categories.

Speech Signal Processing Based on Deep Learning in Complex Acoustic Environments provides a detailed discussion of deep learning-based robust speech processing and its applications. The book begins by looking at the basics of deep learning and common deep network models, followed by front-end algorithms for deep learning-based speech denoising, speech detection, single-channel speech enhancement multi-channel speech enhancement, multi-speaker speech separation, and the applications of deep learning-based speech denoising in speaker verification and speech recognition. - Provides a comprehensive introduction to the development of deep learning-based robust speech processing - Covers speech detection, speech enhancement, dereverberation, multi-speaker speech separation, robust speaker verification, and robust speech recognition - Focuses on a historical overview and then covers methods that demonstrate outstanding performance in practical applications

Robust Automatic Speech Recognition

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Author : Jinyu Li
language : en
Publisher: Academic Press
Release Date : 2015-10-30

Robust Automatic Speech Recognition written by Jinyu Li and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-10-30 with Technology & Engineering categories.

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

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.

Springer Handbook Of Speech Processing

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Author : Jacob Benesty
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-11-28

Springer Handbook Of Speech Processing written by Jacob Benesty 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 2007-11-28 with Technology & Engineering categories.

This handbook plays a fundamental role in sustainable progress in speech research and development. With an accessible format and with accompanying DVD-Rom, it targets three categories of readers: graduate students, professors and active researchers in academia, and engineers in industry who need to understand or implement some specific algorithms for their speech-related products. It is a superb source of application-oriented, authoritative and comprehensive information about these technologies, this work combines the established knowledge derived from research in such fast evolving disciplines as Signal Processing and Communications, Acoustics, Computer Science and Linguistics.

Speech Dereverberation

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Author : Patrick A. Naylor
language : en
Publisher: Springer Science & Business Media
Release Date : 2010-07-27

Speech Dereverberation written by Patrick A. Naylor 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 2010-07-27 with Technology & Engineering categories.

Speech Dereverberation gathers together an overview, a mathematical formulation of the problem and the state-of-the-art solutions for dereverberation. Speech Dereverberation presents current approaches to the problem of reverberation. It provides a review of topics in room acoustics and also describes performance measures for dereverberation. The algorithms are then explained with mathematical analysis and examples that enable the reader to see the strengths and weaknesses of the various techniques, as well as giving an understanding of the questions still to be addressed. Techniques rooted in speech enhancement are included, in addition to a treatment of multichannel blind acoustic system identification and inversion. The TRINICON framework is shown in the context of dereverberation to be a generalization of the signal processing for a range of analysis and enhancement techniques. Speech Dereverberation is suitable for students at masters and doctoral level, as well as established researchers.

Speech Enhancement

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Author : Philipos C. Loizou
language : en
Publisher: CRC Press
Release Date : 2013-02-25

Speech Enhancement written by Philipos C. Loizou and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-02-25 with Technology & Engineering categories.

With the proliferation of mobile devices and hearing devices, including hearing aids and cochlear implants, there is a growing and pressing need to design algorithms that can improve speech intelligibility without sacrificing quality. Responding to this need, Speech Enhancement: Theory and Practice, Second Edition introduces readers to the basic problems of speech enhancement and the various algorithms proposed to solve these problems. Updated and expanded, this second edition of the bestselling textbook broadens its scope to include evaluation measures and enhancement algorithms aimed at improving speech intelligibility. Fundamentals, Algorithms, Evaluation, and Future Steps Organized into four parts, the book begins with a review of the fundamentals needed to understand and design better speech enhancement algorithms. The second part describes all the major enhancement algorithms and, because these require an estimate of the noise spectrum, also covers noise estimation algorithms. The third part of the book looks at the measures used to assess the performance, in terms of speech quality and intelligibility, of speech enhancement methods. It also evaluates and compares several of the algorithms. The fourth part presents binary mask algorithms for improving speech intelligibility under ideal conditions. In addition, it suggests steps that can be taken to realize the full potential of these algorithms under realistic conditions. What’s New in This Edition Updates in every chapter A new chapter on objective speech intelligibility measures A new chapter on algorithms for improving speech intelligibility Real-world noise recordings (on accompanying CD) MATLAB® code for the implementation of intelligibility measures (on accompanying CD) MATLAB and C/C++ code for the implementation of algorithms to improve speech intelligibility (on accompanying CD) Valuable Insights from a Pioneer in Speech Enhancement Clear and concise, this book explores how human listeners compensate for acoustic noise in noisy environments. Written by a pioneer in speech enhancement and noise reduction in cochlear implants, it is an essential resource for anyone who wants to implement or incorporate the latest speech enhancement algorithms to improve the quality and intelligibility of speech degraded by noise. Includes a CD with Code and Recordings The accompanying CD provides MATLAB implementations of representative speech enhancement algorithms as well as speech and noise databases for the evaluation of enhancement algorithms.

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.

Machine Learning Algorithms For Signal And Image Processing

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Author : Deepika Ghai
language : en
Publisher: John Wiley & Sons
Release Date : 2022-11-18

Machine Learning Algorithms For Signal And Image Processing written by Deepika Ghai and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-11-18 with Technology & Engineering categories.

Machine Learning Algorithms for Signal and Image Processing Enables readers to understand the fundamental concepts of machine and deep learning techniques with interactive, real-life applications within signal and image processing Machine Learning Algorithms for Signal and Image Processing aids the reader in designing and developing real-world applications using advances in machine learning to aid and enhance speech signal processing, image processing, computer vision, biomedical signal processing, adaptive filtering, and text processing. It includes signal processing techniques applied for pre-processing, feature extraction, source separation, or data decompositions to achieve machine learning tasks. Written by well-qualified authors and contributed to by a team of experts within the field, the work covers a wide range of important topics, such as: Speech recognition, image reconstruction, object classification and detection, and text processing Healthcare monitoring, biomedical systems, and green energy How various machine and deep learning techniques can improve accuracy, precision rate recall rate, and processing time Real applications and examples, including smart sign language recognition, fake news detection in social media, structural damage prediction, and epileptic seizure detection Professionals within the field of signal and image processing seeking to adapt their work further will find immense value in this easy-to-understand yet extremely comprehensive reference work. It is also a worthy resource for students and researchers in related fields who are looking to thoroughly understand the historical and recent developments that have been made in the field.

Audio Source Separation

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Author : Shoji Makino
language : en
Publisher: Springer
Release Date : 2018-03-01

Audio Source Separation written by Shoji Makino and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-03-01 with Technology & Engineering categories.

This book provides the first comprehensive overview of the fascinating topic of audio source separation based on non-negative matrix factorization, deep neural networks, and sparse component analysis. The first section of the book covers single channel source separation based on non-negative matrix factorization (NMF). After an introduction to the technique, two further chapters describe separation of known sources using non-negative spectrogram factorization, and temporal NMF models. In section two, NMF methods are extended to multi-channel source separation. Section three introduces deep neural network (DNN) techniques, with chapters on multichannel and single channel separation, and a further chapter on DNN based mask estimation for monaural speech separation. In section four, sparse component analysis (SCA) is discussed, with chapters on source separation using audio directional statistics modelling, multi-microphone MMSE-based techniques and diffusion map methods. The book brings together leading researchers to provide tutorial-like and in-depth treatments on major audio source separation topics, with the objective of becoming the definitive source for a comprehensive, authoritative, and accessible treatment. This book is written for graduate students and researchers who are interested in audio source separation techniques based on NMF, DNN and SCA.

Acoustic Echo And Noise Control

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Author : Eberhard Hänsler
language : en
Publisher: John Wiley & Sons
Release Date : 2005-02-04

Acoustic Echo And Noise Control written by Eberhard Hänsler and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005-02-04 with Science categories.

Authors are well known and highly recognized by the "acoustic echo and noise community." Presents a detailed description of practical methods to control echo and noise Develops a statistical theory for optimal control parameters and presents practical estimation and approximation methods