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Automatic Speech Recognition: A Deep Learning Approach (Signals and Communic...

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eBay item number:156720932921
Last updated on May 12, 2025 15:08:24 PDTView all revisionsView all revisions

Item specifics

Condition
Good: A book that has been read but is in good condition. Very minimal damage to the cover including ...
Release Year
2014
Book Title
Automatic Speech Recognition: A Deep Learning Approach (Signal...
ISBN
9781447157786
Subject Area
Computers, Technology & Engineering
Publication Name
Automatic Speech Recognition : a Discriminative and Hierarchical Modeling Approach
Publisher
Springer London, The Limited
Item Length
9.3 in
Subject
Signals & Signal Processing, Speech & Audio Processing, Enterprise Applications / General, Acoustics & Sound
Publication Year
2014
Series
Signals and Communication Technology Ser.
Type
Textbook
Format
Hardcover
Language
English
Author
Li Deng, Dong Yu
Item Weight
227.4 Oz
Item Width
6.1 in
Number of Pages
Xxvi, 321 Pages

About this product

Product Identifiers

Publisher
Springer London, The Limited
ISBN-10
1447157788
ISBN-13
9781447157786
eBay Product ID (ePID)
201594776

Product Key Features

Number of Pages
Xxvi, 321 Pages
Language
English
Publication Name
Automatic Speech Recognition : a Discriminative and Hierarchical Modeling Approach
Subject
Signals & Signal Processing, Speech & Audio Processing, Enterprise Applications / General, Acoustics & Sound
Publication Year
2014
Type
Textbook
Author
Li Deng, Dong Yu
Subject Area
Computers, Technology & Engineering
Series
Signals and Communication Technology Ser.
Format
Hardcover

Dimensions

Item Weight
227.4 Oz
Item Length
9.3 in
Item Width
6.1 in

Additional Product Features

Intended Audience
Scholarly & Professional
Dewey Edition
23
Reviews
"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), "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)
Number of Volumes
1 vol.
Illustrated
Yes
Dewey Decimal
006.454
Table Of Content
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.
Synopsis
This book reviews past and present work on discriminative and hierarchical models for both acoustic and language modeling. It also analyzes the research direction and trends towards establishing future-generation speech recognition., 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., 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.
LC Classification Number
TK5102.9

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