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Automatic speech recognition[electronic resource] :a deep learning approach /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
杜威分類號:	006.454
書名/作者:	Automatic speech recognition : a deep learning approach // by Dong Yu, Li Deng.
作者:	Yu, Dong.
其他作者:	Deng, Li.
出版者:	London : : Springer London :, 2015.
面頁冊數:	xxvi, 321 p. : : ill., digital ;; 24 cm.
Contained By:	Springer eBooks
標題:	Automatic speech recognition.
標題:	Engineering.
標題:	Signal, Image and Speech Processing.
標題:	Engineering Acoustics.
標題:	Computer Appl. in Social and Behavioral Sciences.
ISBN:	9781447157793 (electronic bk.)
ISBN:	9781447157786 (paper)
內容註:	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.
摘要、提要註:	This book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.
電子資源:	http://dx.doi.org/10.1007/978-1-4471-5779-3

Automatic speech recognition[electronic resource] :a deep learning approach /
Yu, Dong.

Automatic speech recognitiona deep learning approach /[electronic resource] :by Dong Yu, Li Deng. - London :Springer London :2015. - xxvi, 321 p. :ill., digital ;24 cm. - 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 summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.

ISBN: 9781447157793 (electronic bk.)

Standard No.: 10.1007/978-1-4471-5779-3doiSubjects--Topical Terms:

175629
Automatic speech recognition.

LC Class. No.: TK7895.S65

Dewey Class. No.: 006.454

Automatic speech recognition[electronic resource] :a deep learning approach /
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520 $a This book summarizes the recent advancement in the field of automatic speech recognition with a focus on discriminative and hierarchical models. This will be the first automatic speech recognition book to include a comprehensive coverage of recent developments such as conditional random field and deep learning techniques. It presents insights and theoretical foundation of a series of recent models such as conditional random field, semi-Markov and hidden conditional random field, deep neural network, deep belief network, and deep stacking models for sequential learning. It also discusses practical considerations of using these models in both acoustic and language modeling for continuous speech recognition.
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