Yu, Dong.
Automatic Speech Recognition A Deep Learning Approach / [electronic resource] : by Dong Yu, Li Deng. - XXVI, 321 p. 62 illus. online resource. - Signals and Communication Technology, 1860-4862 . - Signals and Communication Technology, .
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.
9781447157793
10.1007/978-1-4471-5779-3 doi
Engineering.
Application software.
Acoustical engineering.
Engineering.
Signal, Image and Speech Processing.
Engineering Acoustics.
Computer Appl. in Social and Behavioral Sciences.
TK5102.9 TA1637-1638 TK7882.S65
621.382
Automatic Speech Recognition A Deep Learning Approach / [electronic resource] : by Dong Yu, Li Deng. - XXVI, 321 p. 62 illus. online resource. - Signals and Communication Technology, 1860-4862 . - Signals and Communication Technology, .
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.
9781447157793
10.1007/978-1-4471-5779-3 doi
Engineering.
Application software.
Acoustical engineering.
Engineering.
Signal, Image and Speech Processing.
Engineering Acoustics.
Computer Appl. in Social and Behavioral Sciences.
TK5102.9 TA1637-1638 TK7882.S65
621.382