最尤スペクトル推定法をもちいた音声情報圧縮
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概要
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In order to achieve a speech compression of high quality, it is necessary to extract, as accurately as possible, feature parameter, such as driving source parameter and spectral parameters, and to reproduced these features of the original speech. The purpose of this paper is to give a brief review on speech compression systems and to propose a new method of statistical speech signal processing for extraction of the spectral envelope and the driving source characteristics, and its application to speech compressing system. At first, the theory of the maximum likelihood spectral estimation is discussed and it is shown that the spectral parameters are extracted by solving linear system of equations with short time autocorrelationas its coefficients. Secondly, the modified autocorrelation method for accurate pitch determination is proposed, by which the ill effects of the spectral envelope appearing in the short time autocorrelation are removed by convolving the autocorrelation and the Fourier coefficients of the inverse spectral envelope. Finally, we deal with the problems about speech synthesis from the speech parameters and the result of computer simulation of this method is described. The quality of speech output was measured by means of an articulation test, from which the articulation reference equivalents are determined. It is shown that the analysis synthesis speech compression system can compress speech information to 5, 000 bits/sec at the expence of 3 dB articulation reference equivalent.
- 社団法人日本音響学会の論文
- 1971-09-10
著者
関連論文
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- PARCOR係数の非線形量子化と不均一標本化による音声の能率的符号化
- PARCOR形音声分析合成系
- 音声情報高速処理装置
- 最尤スペクトル推定法をもちいた音声情報圧縮
- 音声スペクトルの統計的最適識別法
- スペクトル符号化に基づく音声分析合成
- 音声の特徴抽出と情報圧縮
- PARCOR帯域圧縮方式における音声品質向上
- PARCOR形音声分析合成系の音声品質向上