• Title/Summary/Keyword: 변형된 연쇄 상태분할

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Performance Improvement of Continuous Digits Speech Recognition Using the Transformed Successive State Splitting and Demi-syllable Pair (반음절쌍과 변형된 연쇄 상태 분할을 이용한 연속 숫자 음 인식의 성능 향상)

  • Seo Eun-Kyoung;Choi Gab-Keun;Kim Soon-Hyob;Lee Soo-Jeong
    • Journal of Korea Multimedia Society
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    • v.9 no.1
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    • pp.23-32
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    • 2006
  • This paper describes the optimization of a language model and an acoustic model to improve speech recognition using Korean unit digits. Since the model is composed of a finite state network (FSN) with a disyllable, recognition errors of the language model were reduced by analyzing the grammatical features of Korean unit digits. Acoustic models utilize a demisyllable pair to decrease recognition errors caused by inaccurate division of a phone or monosyllable due to short pronunciation time and articulation. We have used the K-means clustering algorithm with the transformed successive state splitting in the feature level for the efficient modelling of feature of the recognition unit. As a result of experiments, 10.5% recognition rate is raised in the case of the proposed language model. The demi-syllable fair with an acoustic model increased 12.5% recognition rate and 1.5% recognition rate is improved in transformed successive state splitting.

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Performance Improvement of Continuous Digits Speech Recognition using the Transformed Successive State Splitting and Demi-syllable pair (반음절쌍과 변형된 연쇄 상태 분할을 이용한 연속 숫자음 인식의 성능 향상)

  • Kim Dong-Ok;Park No-Jin
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.9 no.8
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    • pp.1625-1631
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    • 2005
  • This paper describes an optimization of a language model and an acoustic model that improve the ability of speech recognition with Korean nit digit. Recognition errors of the language model are decreasing by analysis of the grammatical feature of korean unit digits, and then is made up of fsn-node with a disyllable. Acoustic model make use of demi-syllable pair to decrease recognition errors by inaccuracy division of a phone, a syllable because of a monosyllable, a short pronunciation and an articulation. we have used the k-means clustering algorithm with the transformed successive state splining in feature level for the efficient modelling of the feature of recognition unit . As a result of experimentations, $10.5\%$ recognition rate is raised in the case of the proposed language model. The demi-syllable pair with an acoustic model increased $12.5\%$ recognition rate and $1.5\%$ recognition rate is improved in transformed successive state splitting.