| Project/Area Number |
22650034
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| Research Category |
Grant-in-Aid for Challenging Exploratory Research
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| Allocation Type | Single-year Grants |
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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) |
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 |
¥3,340,000 (Direct Cost: ¥2,800,000、Indirect Cost: ¥540,000)
Fiscal Year 2012: ¥780,000 (Direct Cost: ¥600,000、Indirect Cost: ¥180,000)
Fiscal Year 2011: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2010: ¥1,000,000 (Direct Cost: ¥1,000,000)
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| Keywords | 音声情報処理 / プライバシ保護 / 声質変換 / 音源分離 / 音声認識 / 人名抽出 / 人名除去 / 固有名認識 / 個人情報 / 音声除去 / 音声抽出 / 背景音除去 / VQ / NMF / プライバシ処理 / 音声のプライバシ保護 / 音声のプライバシ除去 / 音声の除去 / 音質変換 / 固有名除去 / 音楽重量音声 / ベクトル量子化 |
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| Research Abstract |
Spoken language contains speaker characteristics and contents related to privacy information such as personal names. In this study, we developed mixed sound separation techniques based on Vector Quantization and Non-negative Matrix Factorization (NMF), elimination technique of only speech in mixed sound and conversion technique of speaker characteristics. Finally, we developed a personal name detection/elimination method based on the modification of a language model.
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