| Project/Area Number |
18K18504
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| Research Category |
Grant-in-Aid for Challenging Research (Exploratory)
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| Allocation Type | Multi-year Fund |
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| Review Section |
Medium-sized Section 2:Literature, linguistics, and related fields
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| Research Institution | Shizuoka University |
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Principal Investigator |
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| Project Period (FY) |
2018-06-29 – 2021-03-31
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| Project Status |
Completed (Fiscal Year 2020)
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| Budget Amount *help |
¥6,240,000 (Direct Cost: ¥4,800,000、Indirect Cost: ¥1,440,000)
Fiscal Year 2020: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2019: ¥2,470,000 (Direct Cost: ¥1,900,000、Indirect Cost: ¥570,000)
Fiscal Year 2018: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
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| Keywords | 自然言語処理 / 間 / 生成 / 話し言葉処理 / 対話システム |
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| Outline of Final Research Achievements |
By adopting a model closer to humans, we aim to generate a natural pause like a humans, and the interrupt/backchannel timing during conversations. We further aim to apply such a spoken language processing to dialogue systems. We recorded a spoken language corpus, then trascribed and assigned annotations of backchannel/interrupt timing, etc. We constructed an inference system using these annotations based on speech and linguistic features. We built a dialogue system and implemented an agent which participates in the natural language division of the annual AI Werewolf Contest, where agents automatically play the conversation game "Mafia".
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| Academic Significance and Societal Importance of the Research Achievements |
統計的手法の隆盛により、既存の自然言語処理研究のほとんどは大規模データを取集しやすい書き言葉を前提に研究がおこなわれている。そのために話し言葉の処理性能は未だ不十分なのが現状である。また、人間の言語処理は話し言葉を基盤としている可能性が高く、書き言葉の処理においても話し言葉の処理が有用な可能性があり、「間」をはじめとする音声的な要素も取り込んだシステム構築は、自然言語処理全般に資すると共に、人間の言語処理メカニズムの解明にもつながるものである。
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