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Intelligent Speech Signal Processing investigates 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
Researchers, professionals, and graduate students in computer science & engineering, bioinformatics, and electrical engineering interested in signal processing, signal analysis, speech acquisition, soft computing
- A Real-Time DSP-Based System for Voice Activity Detection and Background Noise Reduction
2. Voice Activity Detection Based Home Automation System for Special Needs People
3. Speech Recognition using Convolutional Neural Networks
4. A Deep Dive into Deep Learning Techniques for solving Spoken Language Identification Problems in Speech Signal processing
5. Convolutional Neural Networks for Raw Speech Recognition
6. Disambiguating Conflicting Classification Results in AVSR
7. Robust Bimodal Hindi speech recognition under adverse noisy conditions
8. Speech Disorder Identification Using Artificial Neural Network and Support Vector Machine: A Comparative Study
9. Large Scale Data based Audio Scene Analysis
10. Automatic Speech to Speech Summarization for Tamil Language
- No. of pages:
- © Academic Press 2019
- 27th March 2019
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Nilanjan Dey is Associate Professor in the Department of Computer Science and Engineering, JIS University, Kolkata, India. He is a visiting fellow of the University of Reading, UK. Previously, he held an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA (2012–2015). He was awarded his PhD from Jadavpur University in 2015. He has authored/edited more than 70 books with Elsevier, CRC Press, and SpringerNature, and published more than 300 papers. He is the Editor-in-Chief of the International Journal of Ambient Computing and Intelligence (IGI Global), Associated Editor of IEEE Access, and International Journal of Information Technology (Springer). He is the Series Co-Editor of Springer Tracts in Nature-Inspired Computing (Springer), Series Co-Editor of Advances in Ubiquitous Sensing Applications for Healthcare (Elsevier), Series Editor of Computational Intelligence in Engineering Problem Solving and Intelligent Signal Processing and Data Analysis (CRC). His main research interests include medical imaging, machine learning, computer aided diagnosis, data mining, etc. He is the Indian Ambassador of the International Federation for Information Processing—Young ICT Group and Senior member of IEEE.
Assistant Professor, Department of Information Technology, Techno India College of Technology, Rajarhat, Kolkata, India
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