| Co-Investigator(Kenkyū-buntansha) |
MATSUBARA Shigeki Nagoya University, Information Technology Center, Associate Professor, 情報連携基盤センター, 助教授 (20303589)
YAMAGUCHI Yukiko Nagoya University, Information Technology Center, Research Assistant, 情報連携基盤センター, 助手 (90239921)
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| Budget Amount *help |
¥16,100,000 (Direct Cost: ¥16,100,000)
Fiscal Year 2005: ¥3,300,000 (Direct Cost: ¥3,300,000)
Fiscal Year 2004: ¥4,900,000 (Direct Cost: ¥4,900,000)
Fiscal Year 2003: ¥7,900,000 (Direct Cost: ¥7,900,000)
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| Research Abstract |
We have developed a technique for dialogue proceesing of utilizing human conversation examples for aiming at the achievement of user-friendly dialogue systems. This method executes most of the modules such as speech understanding, speech generation, and speech planning in a data-driven manner. To use the real dialogue examples as data made the system become possible the following functions : the robust speech understanding byusing a similar case, the human-like spontaneous speech output bynatural expressions, and the extension of the dialogue system by adding the examples, as shown in the below :
(1) Construction of the dialogue examples and their utilization : The large-scale dialogue database was constructed as a data for which the conversation system was able to be used immediately. The CIAIR in-car speech dialogue corpus was used as target data. The tags for morpheme analysis, syntactic analysis, and speech-act analysis, etc.were given to the utterance units.
(2) The development of a
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technique for robust speech understanding : The technique for dialogue understanding was developed for information retrieval domain. This is based on the idea of choosing the most similar sentence to the input utterance sentence from among the spoken dialogue corpus, and regarding the intention of the input utterance sentence as the intention given to the sentence. Actually, the method of measuring the similarity between the utterance sentence and the utterance sentence was designed as a similarity calculation method of using information on the morpheme, the syntax, the key word, the end of sentence form, and the context, etc.
(3) Implementation of the speech dialogue system : The example-based dialogue processing was designed, and implemented as a system of the restaurant guide in the running car. The entire system is composed of the speech understanding, the dialogue control, the speech generation, and the examples database. The effectiveness and realizability of our spoken dialogue processing technique were confirmed by the experiments. Less
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