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Signals and Communication Technology Ser.: Automatic Speech Recognition : A Discriminative and Hierarchical Modeling Approach by Li Deng and Dong Yu (2014, Hardcover)
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About this product
Product Identifiers
PublisherSpringer London, The Limited
ISBN-101447157788
ISBN-139781447157786
eBay Product ID (ePID)201594776
Product Key Features
Number of PagesXxvi, 321 Pages
Publication NameAutomatic Speech Recognition : a Discriminative and Hierarchical Modeling Approach
LanguageEnglish
Publication Year2014
SubjectSignals & Signal Processing, Speech & Audio Processing, Enterprise Applications / General, Acoustics & Sound
TypeTextbook
Subject AreaComputers, Technology & Engineering
AuthorLi Deng, Dong Yu
SeriesSignals and Communication Technology Ser.
FormatHardcover
Dimensions
Item Weight227.4 Oz
Item Length9.3 in
Item Width6.1 in
Additional Product Features
Intended AudienceScholarly & Professional
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)
Dewey Edition23
Number of Volumes1 vol.
IllustratedYes
Dewey Decimal006.454
Table Of ContentSection 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.
SynopsisThis 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 NumberTK5102.9
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