Incorporating knowledge sources into statistical speech recognition

Incorporating Knowledge Sources into Statistical Speech Recognition offers solutions for enhancing the robustness of a statistical automatic speech recognition (ASR) system by incorporating various additional knowledge sources while keeping the training and recognition effort feasible. The authors...

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Main Authors: Sakti, Sakriani, Markov, Konstantin, Nakamura, Satoshi, Minker, Wolfgang
格式: 圖書
語言:English
出版: Springer 2017
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在線閱讀:http://repository.vnu.edu.vn/handle/VNU_123/30632
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機構: Vietnam National University, Hanoi
語言: English
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spelling oai:112.137.131.14:VNU_123-306322020-07-07T04:06:34Z Incorporating knowledge sources into statistical speech recognition Sakti, Sakriani Markov, Konstantin Nakamura, Satoshi Minker, Wolfgang Earth and Environmental Science ; Automatic speech recognition. 006.454 Incorporating Knowledge Sources into Statistical Speech Recognition offers solutions for enhancing the robustness of a statistical automatic speech recognition (ASR) system by incorporating various additional knowledge sources while keeping the training and recognition effort feasible. The authors provide an efficient general framework for incorporating knowledge sources into state-of-the-art statistical ASR systems. This framework, which is called GFIKS (graphical framework to incorporate additional knowledge sources), was designed by utilizing the concept of the Bayesian network (BN) framework. This framework allows probabilistic relationships among different information sources to be learned, various kinds of knowledge sources to be incorporated, and a probabilistic function of the model to be formulated. Incorporating Knowledge Sources into Statistical Speech Recognition demonstrates how the statistical speech recognition system may incorporate additional information sources by utilizing GFIKS at different levels of ASR. The incorporation of various knowledge sources, including background noises, accent, gender and wide phonetic knowledge information, in modeling is discussed theoretically and analyzed experimentally. 2017-04-18T08:07:37Z 2017-04-18T08:07:37Z 2009 Book 978-0-387-85829-6 http://repository.vnu.edu.vn/handle/VNU_123/30632 en 207 p. application/pdf Springer
institution Vietnam National University, Hanoi
building VNU Library & Information Center
country Vietnam
collection VNU Digital Repository
language English
topic Earth and Environmental Science ; Automatic speech recognition.
006.454
spellingShingle Earth and Environmental Science ; Automatic speech recognition.
006.454
Sakti, Sakriani
Markov, Konstantin
Nakamura, Satoshi
Minker, Wolfgang
Incorporating knowledge sources into statistical speech recognition
description Incorporating Knowledge Sources into Statistical Speech Recognition offers solutions for enhancing the robustness of a statistical automatic speech recognition (ASR) system by incorporating various additional knowledge sources while keeping the training and recognition effort feasible. The authors provide an efficient general framework for incorporating knowledge sources into state-of-the-art statistical ASR systems. This framework, which is called GFIKS (graphical framework to incorporate additional knowledge sources), was designed by utilizing the concept of the Bayesian network (BN) framework. This framework allows probabilistic relationships among different information sources to be learned, various kinds of knowledge sources to be incorporated, and a probabilistic function of the model to be formulated. Incorporating Knowledge Sources into Statistical Speech Recognition demonstrates how the statistical speech recognition system may incorporate additional information sources by utilizing GFIKS at different levels of ASR. The incorporation of various knowledge sources, including background noises, accent, gender and wide phonetic knowledge information, in modeling is discussed theoretically and analyzed experimentally.
format Book
author Sakti, Sakriani
Markov, Konstantin
Nakamura, Satoshi
Minker, Wolfgang
author_facet Sakti, Sakriani
Markov, Konstantin
Nakamura, Satoshi
Minker, Wolfgang
author_sort Sakti, Sakriani
title Incorporating knowledge sources into statistical speech recognition
title_short Incorporating knowledge sources into statistical speech recognition
title_full Incorporating knowledge sources into statistical speech recognition
title_fullStr Incorporating knowledge sources into statistical speech recognition
title_full_unstemmed Incorporating knowledge sources into statistical speech recognition
title_sort incorporating knowledge sources into statistical speech recognition
publisher Springer
publishDate 2017
url http://repository.vnu.edu.vn/handle/VNU_123/30632
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