Presentation 2004/12/15
Structuring Baseball Live Game Based on Knowledge Dependent Speech Recognition
Atsushi SAKO, Yasuo ARIKI,
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Abstract(in English) The purpose of this study is to automatically structure sports live speech, especially baseball live speech using Large Vocabulary Continuous Speech Recognition system. Since it is a difficult problem to recognize baseball live speech. We propose in this paper a speech recognition method of incorporating the baseball game knowledge such as counting of inning, out, strike, ball and announcer's emotion. This method is formalized in the framework of probability theory and implemented in the conventional speech decoding (Viterbi) algorithm. This method enables to seek a word sequence as well as a structure sequence. The experimental results showed that the proposed approach improved the structuring and segmentation accuracy to 73.3% as well as keywords accuracy by 2.3%.
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Keyword(in English) structuring / language model / information integration / HMM acoustic model / live sports
Paper # NLC2004-96,SP2004-136
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Committee NLC
Conference Date 2004/12/15(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Structuring Baseball Live Game Based on Knowledge Dependent Speech Recognition
Sub Title (in English)
Keyword(1) structuring
Keyword(2) language model
Keyword(3) information integration
Keyword(4) HMM acoustic model
Keyword(5) live sports
1st Author's Name Atsushi SAKO
1st Author's Affiliation Graduated School of Science and Technology, Kobe University()
2nd Author's Name Yasuo ARIKI
2nd Author's Affiliation Faculty of Engineering, Kobe University
Date 2004/12/15
Paper # NLC2004-96,SP2004-136
Volume (vol) vol.104
Number (no) 540
Page pp.pp.-
#Pages 6
Date of Issue