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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
- 2nd April 2019
- Academic Press
- Paperback ISBN:
- eBook ISBN:
Nilanjan Dey received his Ph. D. Degree from Jadavpur University, India, in 2015. He is an Assistant Professor in the Department of Information Technology, Techno International New Town, Kolkata, W.B., India. He holds an honorary position of Visiting Scientist at Global Biomedical Technologies Inc., CA, USA and Research Scientist of Laboratory of Applied Mathematical Modeling in Human Physiology, Territorial Organization of- Scientific and Engineering Unions, Bulgaria. Associate Researcher of Laboratoire RIADI, University of Manouba, Tunisia. His research topic is Medical Imaging, Data mining, Machine learning, Computer Aided Diagnosis, Atherosclerosis etc. He is the Editor-in-Chief of International Journal of Ambient Computing and Intelligence (IGI Global), US, International Journal of Rough Sets and Data Analysis (IGI Global), US, the International Journal of Synthetic Emotions (IGI Global), US, (Co-EinC) and International Journal of Natural Computing Research (IGI Global), US. Series Editor (Co.) of Advances in Ubiquitous Sensing Applications for Healthcare (AUSAH), Elsevier, Advances in Geospatial Technologies (AGT) Book Series, (IGI Global), US, Executive Editor of International Journal of Image Mining (IJIM), Inderscience, Associated Editor of IEEE Access and International Journal of Information Technology, Springer. He has 20 books and more than 200 research articles in peer-reviewed journals and international conferences. He is the organizing committee member of several international conferences including ITITS, W4C, ICMIR, FICTA, ICICT.
Assistant Professor, Department of Information Technology, Techno International New Town, Kolkata, India