<P>THIS BOOK PROVIDES A COMPREHENSIVE OVERVIEW OF THE RECENT ADVANCEMENT IN THE FIELD OF AUTOMATIC SPEECH RECOGNITION WITH A FOCUS ON DEEP LEARNING MODELS INCLUDING DEEP NEURAL NETWORKS AND MANY OF THEIR VARIANTS. THIS IS THE FIRST AUTOMATIC SPEECH RECOGNITION BOOK DEDICATED TO THE DEEP LEARNING APPROACH. IN ADDITION TO THE RIGOROUS MATHEMATICAL TREATMENT OF THE SUBJECT, THE BOOK ALSO PRESENTS INSIGHTS AND THEORETICAL FOUNDATION OF A SERIES OF HIGHLY SUCCESSFUL DEEP LEARNING MODELS.</P>

Cr�ticas:

“Deep Learning (DL) has demonstrated a phenomenal success in various AI applications. ... This book by two leading experts in Deep Learning is certainly a welcome addition to the literature of the field, particularly in automatic speech recognition. ... this book presents a very valuable vista of the state-of-art of Deep Learning, focusing on speech recognition applications.” (Robert Kozma, Mathematical Reviews, September, 2017)

“The book addresses real-world problems of current interest regarding automatic speech recognition. ... This book is useful for all researchers working in automatic speech recognition as well as in real-world applications of deep learning.” (Ruxandra Stoean, zbMATH 1356.68004, 2017)

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