Deep Learning for Speech Signal Classification: A CNN-LSTM Approach

K., Dr. RAGUPATHY; M., Arun; T., Dr. ANAND

ISBN 10: 6208432790 / ISBN 13: 9786208432799

Verlag: LAP LAMBERT Academic Publishing, 2025

Beschreibung

Print on Demand.

Bestandsnummer des Verkäufers 409515997

Bibliografische Details

• Titel: Deep Learning for Speech Signal Classification: A CNN-LSTM Approach
• Verlag: LAP LAMBERT Academic Publishing
• Erscheinungsjahr: 2025
• Sprache: Englisch
• ISBN-10: 6208432790
• ISBN-13: 9786208432799
• Einband: Softcover
• Zustand: New

Über diesen Titel

Inhaltsangabe

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.