Robust Method of Distance Estimation to a Speaker for Spoken Dialog System
| Project/Area Number |
26330211
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Multi-year Fund |
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| Section | 一般 |
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| Research Field |
Perceptual information processing
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| Research Institution | Aichi University of Technology |
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Principal Investigator |
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| Co-Investigator(Renkei-kenkyūsha) |
TAKEDA Kazuya 名古屋大学, 大学院情報科学研究科, 教授 (20273295)
SHIKANO Kiyohiro 奈良先端科学技術大学院大学, 名誉教授 (00263426)
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| Project Period (FY) |
2014-04-01 – 2018-03-31
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| Project Status |
Completed (Fiscal Year 2017)
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| Budget Amount *help |
¥4,810,000 (Direct Cost: ¥3,700,000、Indirect Cost: ¥1,110,000)
Fiscal Year 2017: ¥910,000 (Direct Cost: ¥700,000、Indirect Cost: ¥210,000)
Fiscal Year 2016: ¥1,560,000 (Direct Cost: ¥1,200,000、Indirect Cost: ¥360,000)
Fiscal Year 2015: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2014: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
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| Keywords | 音声認識 / 音声対話システム / 音源距離推定 / 音響モデル / VQコードブック / 深層学習 / Deep Belief Network / 発話者距離推定 / Deep Neural Network |
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| Outline of Final Research Achievements |
We propose the estimation method of distance from a mouth of a speaker to a microphone by estimating and classifying the feature of speech recorded by a single microphone. A Deep Neural Network (DNN) is training using speech data recorded for each distance. For estimation, short-time speech frames are entered into the DNN, it will estimate the distance for each frame. After that, the estimated distance is obtained for one utterance by majority decision of estimated distance in all frames. In speech recognition experiments of 1 m and 5 m, the proposed method can obtain about 85 % identification rate.
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Report
(5 results)
Research Products
(4 results)
