2016 Fiscal Year Final Research Report
Voice-pathology analysis based on automatic topology generation of glottal source HMM
Project/Area Number |
26330216
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Research Category |
Grant-in-Aid for Scientific Research (C)
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Allocation Type | Multi-year Fund |
Section | 一般 |
Research Field |
Perceptual information processing
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Research Institution | National Institute of Advanced Industrial Science and Technology |
Principal Investigator |
SASOU AKIRA 国立研究開発法人産業技術総合研究所, 知能システム研究部門, 主任研究員 (50318169)
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Project Period (FY) |
2014-04-01 – 2017-03-31
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Keywords | 音声分析 / 声帯音源 / AR-HMM |
Outline of Final Research Achievements |
Voice-pathology detection from a subject's voice is a promising technology for the pre-diagnosis of larynx diseases. Glottal source estimation in particular plays a very important role in voice-pathology analysis. To more accurately estimate the spectral envelope and glottal source of the pathology voice, we propose a method that can automatically generate the topology of the Glottal Source Hidden Markov Model, as well as estimate the Auto-Regressive (AR)-HMM parameter by combining the AR-HMM parameter estimation method and the Minimum Description Length-based Successive State Splitting algorithm.
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Free Research Field |
音声・音響信号処理
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