Deep Learning for Speech Signal Classification
A CNN-LSTM Approach
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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 f...
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.
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