| Project/Area Number |
23240023
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| Research Category |
Grant-in-Aid for Scientific Research (A)
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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 | The University of Tokyo (2014-2015)
Nara Institute of Science and Technology (2011-2013) |
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Principal Investigator |
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| Co-Investigator(Kenkyū-buntansha) |
SHIKANO Kiyohiro 奈良先端科学技術大学院大学, 情報科学研究科, 名誉教授 (00263426)
TODA Tomoki 奈良先端科学技術大学院大学, 情報科学研究科, 准教授 (90403328)
KAWANAMI Hiromichi 奈良先端科学技術大学院大学, 情報科学研究科, 助教 (80335489)
ONO Nobutaka 国立情報学研究所, 情報学プリンシプル研究系, 准教授 (80334259)
MIYABE Shigeki 筑波大学, 大学院システム情報工学研究科, 助教 (50598745)
MAKINO Shoji 筑波大学, 大学院システム情報工学研究科, 教授 (60396190)
KOYAMA Shoichi 東京大学, 大学院情報理工学系研究科, 助教 (80734459)
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| Project Period (FY) |
2011-04-01 – 2016-03-31
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| Project Status |
Completed (Fiscal Year 2015)
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| Budget Amount *help |
¥47,840,000 (Direct Cost: ¥36,800,000、Indirect Cost: ¥11,040,000)
Fiscal Year 2014: ¥11,700,000 (Direct Cost: ¥9,000,000、Indirect Cost: ¥2,700,000)
Fiscal Year 2013: ¥11,700,000 (Direct Cost: ¥9,000,000、Indirect Cost: ¥2,700,000)
Fiscal Year 2012: ¥11,700,000 (Direct Cost: ¥9,000,000、Indirect Cost: ¥2,700,000)
Fiscal Year 2011: ¥12,740,000 (Direct Cost: ¥9,800,000、Indirect Cost: ¥2,940,000)
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| Keywords | 音声情報処理 / 統計的学習理論 / 音響信号処理 / 音情報処理 / 音源分離 / 音声認識 |
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| Outline of Final Research Achievements |
In this study, we address an unsupervised custom-made augmented speech communication system based on the higher-order statistics pursuit. This system consists of two parts, namely, a binaural hearing aid using blind source separation and a speaking aid via speech conversion. The following results are obtained. (1) As the binaural hearing-aid system, we propose new algorithms for an accurate and fast blind source separation and statistical speech conversion, yielding a high quality speech enhancement system utilizing a fixed point of auditory perception. (2) As the speaking-aid system, a new robust speech conversion algorithm against a mismatch between speech database is proposed. The evaluation using real-world sound database shows the efficacy of the proposed method.
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