Presentation | 1999/6/18 Statistical Language Model Incorporating Kana-Characters and Phrases Masao Utiyama, Hiroshi Matsumoto, |
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Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | This papre proposes a type of statistical language model which deals with out-of-vocabulary words (OOVs) encountered in very large continuous speech recognition. The proposed language model has a dictionary which contains syllables and phrases as well as words. By using this model, OOVs in speech signals are recognized as sequences of syllables. Then, the transcribed syllable sequences are translated into ordinary words by using a large dictionary which may contain OOVs of the speech recognition system. The experiments showed that the recognition accuracy of a bigram language model increased from 64.35% to 72.53% and that of a trigram language model increased from 70.73% to 82.14%. The recall of the detection of sentences which contain OOVs is 93.0% and the precision is 91.7%. The recall of the detection of OOVs 75.4% and the precision is 78.3%. The ratio of successfully transcribed OOVs is 65.3%. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | statistical language model / speech recognition / out of vocabulary word |
Paper # | SP99-38 |
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Conference Information | |
Committee | SP |
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Conference Date | 1999/6/18(1days) |
Place (in Japanese) | (See Japanese page) |
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Topics (in Japanese) | (See Japanese page) |
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Paper Information | |
Registration To | Speech (SP) |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | Statistical Language Model Incorporating Kana-Characters and Phrases |
Sub Title (in English) | |
Keyword(1) | statistical language model |
Keyword(2) | speech recognition |
Keyword(3) | out of vocabulary word |
1st Author's Name | Masao Utiyama |
1st Author's Affiliation | Shinshu University() |
2nd Author's Name | Hiroshi Matsumoto |
2nd Author's Affiliation | Shinshu University |
Date | 1999/6/18 |
Paper # | SP99-38 |
Volume (vol) | vol.99 |
Number (no) | 121 |
Page | pp.pp.- |
#Pages | 8 |
Date of Issue |