| Project/Area Number |
02555067
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| Research Category |
Grant-in-Aid for Developmental Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
情報工学
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| Research Institution | Toyohashi University of Technology |
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Principal Investigator |
NAKAGAWA Seiichi Toyohashi University of Technology, Department of Information & Computer Sciences, Professor, 工学部, 教授 (20115893)
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| Co-Investigator(Kenkyū-buntansha) |
HAMADA Masahiro Matsushita Electric Industrial Co.,LTD, Central Research Laboratories, Researche, 中央研究所, 研究員
TSUBOKA Eiichi Matsushita Electric Industrial Co., LTD, Central Research, 中央研究所, 室長
YAMAMOTO Mikio Toyohashi University of Technology, Department of Information & Computer Science, 工学部, 助手 (40210562)
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| Project Period (FY) |
1990 – 1992
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| Project Status |
Completed (Fiscal Year 1992)
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| Budget Amount *help |
¥10,600,000 (Direct Cost: ¥10,600,000)
Fiscal Year 1992: ¥1,000,000 (Direct Cost: ¥1,000,000)
Fiscal Year 1991: ¥1,500,000 (Direct Cost: ¥1,500,000)
Fiscal Year 1990: ¥8,100,000 (Direct Cost: ¥8,100,000)
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| Keywords | speech recognition / speech understanding / spoken dialog / hidden Markov model / syntactic analysis / dialog model / 並列処理 / 構文分析 |
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| Research Abstract |
We developed the spoken Japanese dialog system. This dialog system is in the closed world of sightseeing guide. The system guides the information about singhtseeing, and user can input to the system through natural language speech. This sysem consists of speech recognition part, sentence understanding part, dialog proessing part, user utterance prediction part, and so on.
The speech recognition part recognized the input speech using syllable HMMs (Hidden Markov Model) that model the syllables of speech. CFG (Context Free Grammar) is used for modeling the linguistical restriction of user utterances.
In the sentence understanding part, the text obtained form the speech recognition is processed using Japanese lexicon and KAKARIUKE rules (dependency grammar), then transformed to the semantic network using case frames.
In the dialog processing part, the ellipsis complement and pronoun reference are performed, then the dialog is proceeded by the interpretation of the dialog rules. This dialog rules can easily adjusted to the various situations.
In the dialog, ambiguities of meanings of input sentences often occur. The part of dialog for clarification and verification is performed to disambiguate them. The system leads the user and asks the user a question positively to get the information for the disambiguation. There process can make the dialog certainly.
On such a limitative task domain, however, user tends to speak various sentence types, so it is difficult to recognize the speech correctly. The user utterance prediction part predicts the word/syntax of user's utterance for the system's response to improve the reliability of spoken dialog between the system and user.
On the system evaluation, we got the enough speech recognition rate for progressing the dialog, The dialog system could converse with a user naturally.
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