Deep Learning Approaches for Spoken and Natural Language Processing (Hardcover, 1st ed. 2021)

This book provides insights into how deep learning techniques impact language and speech processing applications. The authors discuss the promise, limits and the new challenges in deep learning. The book covers the major differences between the various applications of deep learning and the classical machine learning techniques. The main objective of the book is to present a comprehensive survey of the major applications and research oriented articles based on deep learning techniques that are focused on natural language and speech signal processing. The book is relevant to academicians, research scholars, industrial experts, scientists and post graduate students working in the field of speech signal and natural language processing and would like to add deep learning to enhance capabilities of their work. Discusses current research challenges and future perspective about how deep learning techniques can be applied to improve NLP and speech processing applications; Presents and escalates the research trends and future direction of language and speech processing; Includes theoretical research, experimental results, and applications of deep learning.

General

Imprint:	Springer Nature Switzerland AG
Country of origin:	Switzerland
Series:	Signals and Communication Technology
Release date:	December 2021
First published:	2021
Editors:	Virender Kadyan • Amitoj Singh • Mohit Mittal • Laith Abualigah
Dimensions:	235 x 155mm (L x W)
Format:	Hardcover
Pages:	165
Edition:	1st ed. 2021
ISBN-13:	978-3-03-079777-5
Categories:	Books > Language & Literature > Language & linguistics > Computational linguistics Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-03-079777-5
Barcode:	9783030797775

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