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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
1. A Real-Time DSP-Based System for Voice Activity Detection and Background Noise Reduction2. Voice Activity Detection Based Home Automation System for Special Needs People3. Speech Recognition using Convolutional Neural Networks4. A Deep Dive into Deep Learning Techniques for solving Spoken Language Identification Problems in Speech Signal processing5. Convolutional Neural Networks for Raw Speech Recognition6. Disambiguating Conflicting Classification Results in AVSR7. Robust Bimodal Hindi speech recognition under adverse noisy conditions8. Speech Disorder Identification Using Artificial Neural Network and Support Vector Machine: A Comparative Study9. Large Scale Data based Audio Scene Analysis10. Automatic Speech to Speech Summarization for Tamil Language
