Identification of ARMA Speech Models Using an Effective Representation of Voice Source(Speech and Hearing)
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概要
- 論文の詳細を見る
A two-stage least square identification method is proposed for estimating ARMA (autoregressive moving average) coefficients from speech signals. A pulse-train like input sequence is often employed to account for the source effects in estimating vocal tract parameters of voiced speech. Due to glottal and radiation effects, the pulse train, however, does not represent the effective voice source. The authors have already proposed a simple but effective model of voice source for estimating AR (autoregressive) coefficients. This letter extends our approach to ARMA analysis to wider varieties of speech sounds including nasal vowels and consonants. Analysis results on both synthetic and natural nasal speech are presented to demonstrate the analysis ability of the method.
- 社団法人電子情報通信学会の論文
- 2007-05-01
著者
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Rahman M.
Department Of Computer Science And Engineering Shah Jalal University Of Science And Technology
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Rahman M.
Department Of Bioresource Science Ibaraki University College Of Agriculture
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SHIMAMURA Tetsuya
Department of Information and Computer Sciences, Saitama University
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Shimamura Tetsuya
Department Of Information And Computer Sciences Saitama University
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Rahman M.
Department Of Applied Chemistry And Biochemistry Kumamoto University
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