Description
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
Table of Contents
1. Comparative Analysis of Machine Learning Algorithms for Audio Event Classification using Mel Frequency Cepstral Coefficients2. Closed-Set Speaker Identification System based on MFCC and PNCC features in Combination with Different Fusion Strategy3. Kurtosis Data Selective Affine Projection Adaptive Filtering Algorithm for Speech Processing Applications4. A novel approach towards phoneme-to-viseme mapping in Malayalam5. Modified Least Mean Square Adaptive Noise Reduction Algorithm for Speech Enhancement6. Recursive noise estimation-based Wiener filtering for monaural speech enhancement7. Unsupervised Speech Enhancement based on Phase Aware Time-Frequency Mask Estimation
