Robust Speech Features Based on LPC Using Weighted Arcsin Transform

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概要

• 論文の詳細を見る

• To increase the discriminating ability of the speech feature based on linear predictive coding (LPC) and increase its noise robustness, an SNR-dependent arcsin transform is applied to the autocorrelation sequence (ACS) of each analysis frame in a speech signal. Moreover, each component in the ACS is also weighted by the normalized reciprocal of the average magnitude difference function (AMDF) for emphasizing its peak structnre. Experimental results for the task of Mandarin digit recognition indicate that the LPC speech feature employing the proposed scheme is more robust than some widely used LPC-based approaches over a wide range of SNR values.

• 一般社団法人電子情報通信学会の論文
• 2003-02-01

著者

• Hung Wei-wen

  Department Of Electrical Engineering Chang Gung University:department Of Electronic Engineering Ming

• Hung Wei-wen

  Department Of Electrical Engineering Ming-chi Institute Of Technology

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