Detection of acoustic features in human biological sounds based on statistical approach
| Project/Area Number |
20500157
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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 |
Perception information processing/Intelligent robotics
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| Research Institution | Nagasaki University |
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Principal Investigator |
MATSUNAGA Shoichi Nagasaki University, 工学部, 教授 (90380815)
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| Co-Investigator(Kenkyū-buntansha) |
YAMAUCHI Katsuya 長崎大学, 工学研究科, 助教 (10380718)
OGURI Kiyoshi 長崎大学, 工学研究科, 教授 (80325670)
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| Project Period (FY) |
2008 – 2010
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| Project Status |
Completed (Fiscal Year 2010)
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| Budget Amount *help |
¥4,420,000 (Direct Cost: ¥3,400,000、Indirect Cost: ¥1,020,000)
Fiscal Year 2010: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
Fiscal Year 2009: ¥1,300,000 (Direct Cost: ¥1,000,000、Indirect Cost: ¥300,000)
Fiscal Year 2008: ¥1,950,000 (Direct Cost: ¥1,500,000、Indirect Cost: ¥450,000)
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| Keywords | 生体音 / 肺音 / 情動推定 / 特徴パラメータ / 統計的音響モデル |
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| Research Abstract |
In this research project, we devised a novel classification procedure for distinguishing between normal and abnormal respiratory sounds on the basis of stochastic approach. The main characteristic of our procedure is that two stochastic models are used to detect abnormal respiratory sounds precisely: hidden Markov models for acoustic spectral features and bigram models for the occurrence of acoustic segments in each respiratory period. We also devised an approach to the classification of emotion clusters using prosodic features. In our approach, we use the duration ratios of specific acoustic segments-resonant cry segments and silence segments-in the infants' cries as prosodic features. The classification performance of our approach using the segment duration ratios was significantly better than that of the method using spectral features.
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Report
(4 results)
Research Products
(22 results)
