Speech Signal Processing Based On Deep Learning In Complex Acoustic Environments


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


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 : 2024-11-01

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 2024-11-01 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. It 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. The book particularly emphasizes modern deep learning-based techniques for speaker verification and speech recognition, including their foundations and cutting-edge technologies.



New Era For Robust Speech Recognition


New Era For Robust Speech Recognition
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Author : Shinji Watanabe
language : en
Publisher: Springer
Release Date : 2017-10-30

New Era For Robust Speech Recognition written by Shinji Watanabe and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-10-30 with Computers categories.


This book covers the state-of-the-art in deep neural-network-based methods for noise robustness in distant speech recognition applications. It provides insights and detailed descriptions of some of the new concepts and key technologies in the field, including novel architectures for speech enhancement, microphone arrays, robust features, acoustic model adaptation, training data augmentation, and training criteria. The contributed chapters also include descriptions of real-world applications, benchmark tools and datasets widely used in the field. This book is intended for researchers and practitioners working in the field of speech processing and recognition who are interested in the latest deep learning techniques for noise robustness. It will also be of interest to graduate students in electrical engineering or computer science, who will find it a useful guide to this field of research.



Deep Learning Approaches For Spoken And Natural Language Processing


Deep Learning Approaches For Spoken And Natural Language Processing
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Author : Virender Kadyan
language : en
Publisher: Springer Nature
Release Date : 2022-01-01

Deep Learning Approaches For Spoken And Natural Language Processing written by Virender Kadyan and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-01-01 with Technology & Engineering categories.


This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, limits and the new challenges in deep learning. The book covers the major differences between the various applications of deep learning and the classical machine learning techniques. The main objective of the book is to present a comprehensive survey of the major applications and research oriented articles based on deep learning techniques that are focused on natural language and speech signal processing. The book is relevant to academicians, research scholars, industrial experts, scientists and post graduate students working in the field of speech signal and natural language processing and would like to add deep learning to enhance capabilities of their work. Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications; Presents and escalates the research trends and future direction of language and speech processing; Includes theoretical research, experimental results, and applications of deep learning.



Intelligent Speech Signal Processing


Intelligent Speech Signal Processing
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Author : Nilanjan Dey
language : en
Publisher: Academic Press
Release Date : 2019-06-15

Intelligent Speech Signal Processing written by Nilanjan Dey and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-06-15 with Technology & Engineering categories.


Intelligent Speech Signal Processing investigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics related information, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. It provides a forum for readers to discover the characteristics of intelligent speech signal processing systems across different domains. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multi-disciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, implementation, development, and management of intelligent systems, neural networks, and related machine learning techniques for speech signal processing. Highlights different data analytics techniques in speech signal processing, including machine learning, and data mining Illustrates different applications and challenges across the design, implementation, and management of intelligent systems and neural networks techniques for speech signal processing Includes coverage of biomodal speech recognition, voice activity detection, spoken language and speech disorder identification, automatic speech to speech summarization, and convolutional neural networks



Computational Analysis Of Sound Scenes And Events


Computational Analysis Of Sound Scenes And Events
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Author : Tuomas Virtanen
language : en
Publisher: Springer
Release Date : 2017-09-21

Computational Analysis Of Sound Scenes And Events written by Tuomas Virtanen and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-21 with Technology & Engineering categories.


This book presents computational methods for extracting the useful information from audio signals, collecting the state of the art in the field of sound event and scene analysis. The authors cover the entire procedure for developing such methods, ranging from data acquisition and labeling, through the design of taxonomies used in the systems, to signal processing methods for feature extraction and machine learning methods for sound recognition. The book also covers advanced techniques for dealing with environmental variation and multiple overlapping sound sources, and taking advantage of multiple microphones or other modalities. The book gives examples of usage scenarios in large media databases, acoustic monitoring, bioacoustics, and context-aware devices. Graphical illustrations of sound signals and their spectrographic representations are presented, as well as block diagrams and pseudocode of algorithms.



Automatic Speech Recognition


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.



Robust Automatic Speech Recognition


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



Handbook Of Neural Networks For Speech Processing


Handbook Of Neural Networks For Speech Processing
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Author : Shigeru Katagiri
language : en
Publisher: Artech House Publishers
Release Date : 2000

Handbook Of Neural Networks For Speech Processing written by Shigeru Katagiri and has been published by Artech House Publishers this book supported file pdf, txt, epub, kindle and other format this book has been release on 2000 with Computers categories.


Here are the comprehensive details on cutting edge technologies employing neural networks for speech recognition and speech processing in modern communications. Going far beyond the simple speech recognition technologies on the market today, this new book, written by and for speech and signal processing engineers in industry, R&D, and academia, takes you to the forefront of the hottest emergent neural net-based speech processing techniques.



Speech And Audio Processing For Coding Enhancement And Recognition


Speech And Audio Processing For Coding Enhancement And Recognition
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Author : Tokunbo Ogunfunmi
language : en
Publisher: Springer
Release Date : 2014-10-14

Speech And Audio Processing For Coding Enhancement And Recognition written by Tokunbo Ogunfunmi and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-10-14 with Technology & Engineering categories.


This book describes the basic principles underlying the generation, coding, transmission and enhancement of speech and audio signals, including advanced statistical and machine learning techniques for speech and speaker recognition with an overview of the key innovations in these areas. Key research undertaken in speech coding, speech enhancement, speech recognition, emotion recognition and speaker diarization are also presented, along with recent advances and new paradigms in these areas.



Digital Signal Processing In Audio And Acoustical Engineering


Digital Signal Processing In Audio And Acoustical Engineering
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Author : Francis F. Li
language : en
Publisher: CRC Press
Release Date : 2019-04-02

Digital Signal Processing In Audio And Acoustical Engineering written by Francis F. Li and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-02 with Technology & Engineering categories.


Starting with essential maths, fundamentals of signals and systems, and classical concepts of DSP, this book presents, from an application-oriented perspective, modern concepts and methods of DSP including machine learning for audio acoustics and engineering. Content highlights include but are not limited to room acoustic parameter measurements, filter design, codecs, machine learning for audio pattern recognition and machine audition, spatial audio, array technologies and hearing aids. Some research outcomes are fed into book as worked examples. As a research informed text, the book attempts to present DSP and machine learning from a new and more relevant angle to acousticians and audio engineers. Some MATLAB® codes or frameworks of algorithms are given as downloads available on the CRC Press website. Suggested exploration and mini project ideas are given for "proof of concept" type of exercises and directions for further study and investigation. The book is intended for researchers, professionals, and senior year students in the field of audio acoustics.