Study on Adaptive Comb filter for Auditory Scene Analysis
| Project/Area Number |
12650420
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Measurement engineering
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| Research Institution | The University of Electro-Communications |
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Principal Investigator |
NISHI Kazuki Faculty of Electro-Communications, The University of Electro-Communications, Research Assistant, 電気通信学部, 助手 (00208125)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥2,600,000 (Direct Cost: ¥2,600,000)
Fiscal Year 2001: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2000: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Keywords | Quasi-periodic Signal / comb filter / Auditory Scene Analysis / Wiener filter / kalman filter / Stochastic differential equation / constant-Q / Critical Bands / 櫛形フィルタ / ウィーナーフィルタ / 振幅変動 / ピッチ変動 |
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| Research Abstract |
In this study, we have developed optimal filters for quasi-periodic signals involving amplitude and pitch fluctuations (e.g., a real speech or instrumental sound) as a fundamental technology for realization of the auditory scene analysis.
First, we derived linear optimal filters based on the quasi-periodic signal model. The Wiener filter solution under the steady-state condition leads to the constant-BW (-bandwidth)/constant-Q mixed comb structure in which each pass-band located at harmonic frequencies has a constant bandwidth in lower frequency, constant-Q characteristic in higher frequency, and those mixture appears in the intermediate frequency. It is shown that such filter banks closely imitates that of the human auditory system. Next, we derived a Kalman filter based on the Ito stochastic differential equation involving unknown random fluctuations as well as the given slowly varying fluctuations. It is verified that the steady-state solution coincides with the Wiener filter one.
In addition, we have designed digital filters, which have not only a comb structure for extracting each harmonic component but also a notch structure for suppressing interference between harmonics components, based on digitization of the continuous Kalman filter equation. Finally, we have established a filter system for extracting a specific sound from among the mixed sound, and confirmed the validity of utilizing as the front-end processing for speech recognition.
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Report
(3 results)
Research Products
(18 results)
