| Project/Area Number |
03452167
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| Research Category |
Grant-in-Aid for General 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, Faculty of Engineering, Professor, 工学部, 教授 (20115893)
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| Co-Investigator(Kenkyū-buntansha) |
YAMAMOTO Mikio Toyohashi University of Technology, Faculty of Engineering, Assistant, 工学部, 助手 (40210562)
INOUE Katsumi Toyohashi University of Technology, Faculty of Engineering, Lecture, 工学部, 講師 (10252321)
奥山 徹 豊橋技術科学大学, 工学部, 講師 (30177191)
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| Project Period (FY) |
1991 – 1993
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| Project Status |
Completed (Fiscal Year 1993)
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| Budget Amount *help |
¥7,100,000 (Direct Cost: ¥7,100,000)
Fiscal Year 1993: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 1992: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 1991: ¥5,100,000 (Direct Cost: ¥5,100,000)
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| Keywords | Speech Input / Speech Recognition / Dialog System / Spoken Dialog / Ambiguous Input / Speech Understanding / Language Understaning / 自然言語処理 / 自然言語解析 / 文脈処理 / 間投詞 / 言い淀み / 言い直し / 助詞 / 倒置 / 文生成 |
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| Research Abstract |
We proposed an unsupervised speaker adaptation method on sequencial concatenation training that used the theory of MAPE(Maximum A Posteriori probabitity Estimation) for continuous parameter HMM.In this method, we should only specify the syllable label sequence for the utterrance. The label sequences were provided automatically by the recognizer which used a speaker-independent model in advance. The experimental results on continuous speech recognition showed that the better model gave a performance comparable to that of supervised adaptation.
Secondly, we proposed a method to process interjection and unknown words so that a speech recognition system could deal with spontaneous speech in dialog. We have evaluated the peerformance of our speech recognition system using test sentence sets including interjection or unknown words, and confirmed that the proposed method worked well.
Thirdly we investigated the menu-guided spoken natural language understanding system that could understand all user's inputs. This work was motivated by the following fact that a user could not understand what to say or how to say to a computer in natural language. The system displays a menu that consists of acceptable content words and the usur chooses one word from the menu and speaks out phrase that includes the word. The experimental showed that our system performed well for the novice users.
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