Department of Information Technology, Techno India College of Technology, Kolkata, India
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ISBN: 978-0-12-818130-0
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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.