| Project/Area Number |
22300059
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| Research Category |
Grant-in-Aid for Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Perception information processing/Intelligent robotics
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| Research Institution | Toyohashi University of Technology |
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Principal Investigator |
NAKAGAWA Seiichi 豊橋技術科学大学, 大学院・工学研究科, 教授 (20115893)
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| Co-Investigator(Kenkyū-buntansha) |
AKIBA Tomoyoshi 豊橋技術科学大学, 大学院・工学研究科, 准教授 (00356346)
YAMAMOTO Kazumasa 豊橋技術科学大学, 大学院・工学研究科, 准教授 (40324230)
TSUCHIYA Masatoshi 豊橋技術科学大学, 情報メディア基盤センター, 助教 (70378256)
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| Project Period (FY) |
2010 – 2012
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| Project Status |
Completed (Fiscal Year 2012)
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| Budget Amount *help |
¥18,070,000 (Direct Cost: ¥13,900,000、Indirect Cost: ¥4,170,000)
Fiscal Year 2012: ¥5,590,000 (Direct Cost: ¥4,300,000、Indirect Cost: ¥1,290,000)
Fiscal Year 2011: ¥5,720,000 (Direct Cost: ¥4,400,000、Indirect Cost: ¥1,320,000)
Fiscal Year 2010: ¥6,760,000 (Direct Cost: ¥5,200,000、Indirect Cost: ¥1,560,000)
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| Keywords | 音声情報処理 / 音声認識 / 話し言葉 / 書き言葉 / 整形 / 情報検索 / 音声ドキュメント / 音節トライグラム / ｎグラムインデックス / 音声検索語検索 / 音声検索 / 音声入力 / ＧＭＭ / ＨＭＭ / ＤＮＮ / ＨＣＮＦ / 音声整形 / 音声要約 / HMM / トピック依存言語モデル / nグラムインデックス / 未知語 |
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| Research Abstract |
We studied on automatic speech recognition, written style transformation from spoken style transcription and fast term detection for spoken documents. For accurately automatic speech recognition, we proposed a novel speech recognition model beyond the conventional HMM, and showed the effectiveness. For cleaning speech recognition results, we proposed a probabilistic model of cleaning from spoken style with recognition errors to written style and showed the effectiveness. Finally, we proposed a fast term detection method based on tri-gram indexes from the transcription of spoken documents and showed the effectiveness.
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