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Nilanjan Dey - Intelligent Speech Signal Processing

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Nilanjan Dey Intelligent Speech Signal Processing
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Intelligent Speech Signal Processinginvestigates the utilization of speech analytics across several systems and real-world activities, including sharing data analytics, creating collaboration networks between several participants, and implementing video-conferencing in different application areas. Chapters focus on the latest applications of speech data analysis and management tools across different recording systems. The book emphasizes the multidisciplinary nature of the field, presenting different applications and challenges with extensive studies on the design, 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

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Intelligent Speech Signal Processing First Edition Nilanjan Dey Department of - photo 1
Intelligent Speech Signal Processing

First Edition

Nilanjan Dey

Department of Information Technology, Techno India College of Technology, Kolkata, India

Copyright Academic Press is an imprint of Elsevier 125 London Wall London - photo 2

Copyright

Academic Press is an imprint of Elsevier

125 London Wall, London EC2Y 5AS, United Kingdom

525 B Street, Suite 1650, San Diego, CA 92101, United States

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The Boulevard, Langford Lane, Kidlington, Oxford OX5 1GB, United Kingdom

2019 Elsevier Inc. All rights reserved.

No part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopying, recording, or any information storage and retrieval system, without permission in writing from the publisher. Details on how to seek permission, further information about the Publishers permissions policies and our arrangements with organizations such as the Copyright Clearance Center and the Copyright Licensing Agency, can be found at our website: www.elsevier.com/permissions.

This book and the individual contributions contained in it are protected under copyright by the Publisher (other than as may be noted herein).

Notices

Knowledge and best practice in this field are constantly changing. As new research and experience broaden our understanding, changes in research methods, professional practices, or medical treatment may become necessary.

Practitioners and researchers must always rely on their own experience and knowledge in evaluating and using any information, methods, compounds, or experiments described herein. In using such information or methods they should be mindful of their own safety and the safety of others, including parties for whom they have a professional responsibility.

To the fullest extent of the law, neither the Publisher nor the authors, contributors, or editors, assume any liability for any injury and/or damage to persons or property as a matter of products liability, negligence or otherwise, or from any use or operation of any methods, products, instructions, or ideas contained in the material herein.

Library of Congress Cataloging-in-Publication Data

A catalog record for this book is available from the Library of Congress

British Library Cataloguing-in-Publication Data

A catalogue record for this book is available from the British Library

ISBN: 978-0-12-818130-0

For information on all Academic Press publications visit our website at https://www.elsevier.com/books-and-journals

Publisher Mara Conner Acquisition Editor Mara Conner Editorial Project - photo 3

Publisher: Mara Conner

Acquisition Editor: Mara Conner

Editorial Project Manager: Thomas Van Der Ploeg

Production Project Manager: Punithavathy Govindaradjane

Cover Designer: Miles Hitchen

Typeset by SPi Global, India

Contributors

Numbers in parenthesis indicate the pages on which the authors' contributions begin.

Rajesh Kumar Aggarwal 5 National Institute of Technology Kurukshetra, Kurukshetra, India

Mazid Alam 175 Department of CSE, Kaziranga University, Jorhat, India

David Brown 39 Sat-Com (PTY) Ltd., Windhoek, Namibia

Himanish Shekhar Das 81 Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, India

Anilesh Dey 139 Department of Electronics and Communication Engineering, Narula Institute of Technology, Kolkata, India

Smita Dey 175 Department of CSE, Kaziranga University, Jorhat, India

Juan C. Gmez 55 Laboratory for System Dynamics and Signal Processing, Universidad Nacional de Rosario, CIFASIS-CONICET, Rosario, Argentina

Dharm Singh Jat 101 Namibia University of Science and Technology, Windhoek, Namibia

S. Jothilakshmi 113 Department of Information Technology, Annamalai University, Chidambaram, India

Biswajit Karan 153 Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, India

Anton Sokamato Limbo 101 Namibia University of Science and Technology, Windhoek, Namibia

Kartik Mahto 153 Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, India

Rajesh Kumar Muthu 39 Vellore Institute of Technology, Vellore, India

A. NithyaKalyani 113 Department of Computer Science and Engineering, Annamalai University, Chidambaram, India

Vishal Passricha 5 National Institute of Technology Kurukshetra, Kurukshetra, India

Pinki Roy 81 Department of Computer Science and Engineering, National Institute of Technology Silchar, Silchar, India

Gonzalo D. Sad 55 Laboratory for System Dynamics and Signal Processing, Universidad Nacional de Rosario, CIFASIS-CONICET, Rosario, Argentina

Sajal Saha 175 Department of CSE, Kaziranga University, Jorhat, India

Sitanshu Sekhar Sahu 153 Department of Electronics and Communication Engineering, Birla Institute of Technology, Mesra, Ranchi, India

K.C. Santosh 1 Department of Computer Science, The University of South Dakota, Vermillion, SD, United States

Sudhangshu Sarkar 139 Department of Electrical Engineering, Narula Institute of Technology, Kolkata, India

Charu Singh 39, 101

Sat-Com (PTY) Ltd.

Windhoek, Namibia

Lucas D. Terissi 55 Laboratory for System Dynamics and Signal Processing, Universidad Nacional de Rosario, CIFASIS-CONICET, Rosario, Argentina

Maarten Venter 39 Sat-Com (PTY) Ltd., Windhoek, Namibia

About the Editor

Nilanjan Dey is an assistant professor in the Department of Information Technology at Techno India College of Technology, Kolkata. He completed his PhD from Jadavpur University in 2015. He is a visiting fellow at the Wearables Computing Laboratory, Department of Biomedical Engineering University of Reading, UK; visiting professor at the College of Information and Engineering, Wenzhou Medical University, China, and Duy Tan University, Vietnam. He has held the honorary position of visiting scientist at Global Biomedical Technologies Inc., CA, USA (201215).

He is the editor-in-chief of the International Journal of Ambient Computing and Intelligence (IGI Global), series co-editor of Springer Tracts in Nature-Inspired Computing (Springer) and Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH; Elsevier), and series editor for Intelligent Signal Processing and Data Analysis (CRC Press). He has authored/edited more than 40 books for Elsevier, Wiley, CRC Press, and Springer, and published more than 350 research articles. His primary research interests include medical imaging, machine learning, bioinspired computing, data mining, and related fields. He is a life member of the Institute of Engineers (India).

Preface

Intelligent speech signal processing methods have increasingly replaced the conventional analog signal processing methods in several applications, including speech analysis and processing, telecommunications, and tracking. These intelligent speech signal processing approaches support different areas in a variety of everyday problems, multimedia communications, industrial automation, and biometrics. Incorporating different signal processing approaches, such as signal analysis using an analytical signal description, can be combined for efficient speech detection. In intelligent systems, pattern recognition and machine learning methods are vital tools for reasoning under uncertainty. They help to extract significant information from massive data in an automated fashion using statistical and computational methods. This domain is related to probability, statistics, optimization methods, and control theory. The focus is on providing solutions for tasks at which intelligence is inevitably essential. Application domains include computer vision, speech processing, natural language processing, manmachine interfaces, expert systems, and robotics, etc. Typically, there are general attributes that should be included in the intelligent signal processing system, namely nonlinearity, adaptively, and robustness. A speech signal processing device that operates in a nonstationary environment can be considered intelligent once it is able to explore the information content of its input in an efficient mode and at all times.

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