Automatic Speech Recognition

A Deep Learning Approach

Dong Yu, Li Deng

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Hardback

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English

Springer London Ltd
28 November 2014

Acoustic & sound engineering; Imaging systems & technology; Speech recognition

Series: Signals and Communication Technology

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.

By: Dong Yu, Li Deng
Imprint: Springer London Ltd
Country of Publication: United Kingdom
Edition: 2015 ed.
Dimensions: Height: 235mm, Width: 155mm, Spine: 21mm
Weight: 6.447kg
ISBN: 9781447157786
ISBN 10: 1447157788
Series: Signals and Communication Technology
Pages: 321
Publication Date: 28 November 2014
Audience: Professional and scholarly , Undergraduate
Format: Hardback
Publisher's Status: Active

Section 1: Automatic speech recognition: Background.- Feature extraction: basic frontend.- Acoustic model: Gaussian mixture hidden Markov model.- Language model: stochastic N-gram.- Historical reviews of speech recognition research: 1st, 2nd, 3rd, 3.5th, and 4th generations.- Section 2: Advanced feature extraction and transformation.- Unsupervised feature extraction.- Discriminative feature transformation.- Section 3: Advanced acoustic modeling.- Conditional random field (CRF) and hidden conditional random field (HCRF).- Deep-Structured CRF.- Semi-Markov conditional random field.- Deep stacking models.- Deep neural network – hidden Markov hybrid model.- Section 4: Advanced language modeling.- Discriminative Language model.- Log-linear language model.- Neural network language model.

Reviews for Automatic Speech Recognition: A Deep Learning Approach

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)