Isbn: 9786208432799 - deep learning for speech signal classification: a cnn-lstm approach (8 resultados)

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New.

PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

Condición: New. In English.

Taschenbuch. Condición: Neu. Deep Learning for Speech Signal Classification | A CNN-LSTM Approach | Ragupathy K. (u. a.) | Taschenbuch | Englisch | 2025 | LAP LAMBERT Academic Publishing | EAN 9786208432799 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 52 pp. Englisch.

Taschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 52 pp. Englisch.

Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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.…