MAP estimation-based noise suppression and blind source separation using single voice activity detection
| Project/Area Number |
24500204
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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 |
Perception information processing/Intelligent robotics
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| Research Institution | Osaka University |
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Principal Investigator |
KAWAMURA Arata 大阪大学, 基礎工学研究科, 准教授 (60362646)
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| Project Period (FY) |
2012-04-01 – 2015-03-31
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| Project Status |
Completed (Fiscal Year 2014)
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| Budget Amount *help |
¥4,550,000 (Direct Cost: ¥3,500,000、Indirect Cost: ¥1,050,000)
Fiscal Year 2014: ¥1,690,000 (Direct Cost: ¥1,300,000、Indirect Cost: ¥390,000)
Fiscal Year 2013: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2012: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
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| Keywords | 単一話者区間 / 音源分離 / ノイズ除去 / 事後確率最大化 / 統計処理 / MAP推定 / 音源分離性能の改善 / 直交軸射影 / ICA |
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| Outline of Final Research Achievements |
A blind source separation method using two microphones has been investigated. In a practical situation, environmental noise and reverberation exist. Since they degrade source separation quality, we have to remove such undesired effects. To establish an effective blind source separation method, we employ a single voice activity detector which detects single talk segments. These segments give the target source locations. Addition to it, a MAP (maximum a posteriori) estimation-based noise suppressor is introduced as a post-processor for improving the speech quality of the separated signals. Test speech signals are transmitted from loudspeakers and captured at a stereo microphone in a practical reverberant environment. Simulation results showed that the observed speech signals are effectively separated by the proposed method.
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Report
(4 results)
Research Products
(2 results)
