Applied Speech Processing: Algorithms and Case Studies is concerned with supporting and enhancing the utilization of speech analytics in several systems and real-world activities, including sharing data analytics related information, creating collaboration networks between several participants, and the use of video-conferencing in different application areas. The book provides a well-standing forum to discuss the characteristics of the intelligent speech signal processing systems in different domains. The book is proposed for professionals, scientists, and engineers who are involved in new techniques of intelligent speech signal processing methods and systems. It provides an outstanding foundation for undergraduate and post-graduate students as well. - Includes basics of speech data analysis and management tools with several applications, highlighting recording systems - Covers different techniques of big data and Internet-of-Things in speech signal processing, including machine learning and data mining - Offers a multidisciplinary view of current and future challenges in this field, with extensive case studies on the design, implementation, development and management of intelligent systems, neural networks, and related machine learning techniques for speech signal processing

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, Wiley, CRC Press, and Springer, 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.

Applied Speech Processing: Algorithms and Case Studies is concerned with supporting and enhancing the utilization of speech analytics in several systems and real-world activities, including sharing data analytics related information, creating collaboration networks between several participants, and the use of video-conferencing in different application areas. The book provides a well-standing forum to discuss the characteristics of the intelligent speech signal processing systems in different domains. The book is proposed for professionals, scientists, and engineers who are involved in new techniques of intelligent speech signal processing methods and systems. It provides an outstanding foundation for undergraduate and post-graduate students as well.

• Includes basics of speech data analysis and management tools with several applications, highlighting recording systems
• Covers different techniques of big data and Internet-of-Things in speech signal processing, including machine learning and data mining
• Offers a multidisciplinary view of current and future challenges in this field, with extensive case studies on the design, implementation, development and management of intelligent systems, neural networks, and related machine learning techniques for speech signal processing

1. Comparative Analysis of Machine Learning Algorithms for Audio Event Classification using Mel Frequency Cepstral Coefficients 2. Closed-Set Speaker Identification System based on MFCC and PNCC features in Combination with Different Fusion Strategy 3. Kurtosis Data Selective Affine Projection Adaptive Filtering Algorithm for Speech Processing Applications 4. A novel approach towards phoneme-to-viseme mapping in Malayalam 5. Modified Least Mean Square Adaptive Noise Reduction Algorithm for Speech Enhancement 6. Recursive noise estimation-based Wiener filtering for monaural speech enhancement 7. Unsupervised Speech Enhancement based on Phase Aware Time-Frequency Mask Estimation