Deep Learning for Speech Signal Classification - K., Dr. RAGUPATHY;M., Arun;T., Dr. ANAND
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Speech signal classification plays a crucial role in speech recognition, speaker identification, emotion detection, and audio processing. This book provides a comprehensive guide to leveraging deep learning techniques-specifically Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks-for effective speech signal classification.Key Topics Covered:Fundamentals of Speech Processing - Understanding speech signals, spectrograms, and feature extraction techniques like MFCCs. Introduction to Deep Learning - Overview of neural networks, CNNs for feature extraction, and LSTMs…mehr

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Produktbeschreibung
Speech signal classification plays a crucial role in speech recognition, speaker identification, emotion detection, and audio processing. This book provides a comprehensive guide to leveraging deep learning techniques-specifically Convolutional Neural Networks (CNNs) and Long Short-Term Memory (LSTM) networks-for effective speech signal classification.Key Topics Covered:Fundamentals of Speech Processing - Understanding speech signals, spectrograms, and feature extraction techniques like MFCCs. Introduction to Deep Learning - Overview of neural networks, CNNs for feature extraction, and LSTMs for capturing temporal dependencies.CNN-LSTM Hybrid Model - A step-by-step approach to combining CNNs and LSTMs for improved speech classification accuracy.
Autorenporträt
Dr. Ragupathy K holds a Ph.D. in Mechanical Engineering and is a distinguished faculty member at Agni College of Technology. His research expertise lies in Aluminium Metal Matrix Composite materials, focusing on enhancing their properties for advanced engineering applications.