语音识别中一种高效的mel-LPC分析方法

H. Matsumoto, Y. Nakatoh, Y. Furuhata
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引用次数: 26

摘要

本文提出了一种简单且e(cid:14)客户端的时域技术来估计mel-频轴(Mel-LPC)上的全轮询模型。与传统的线性预测分析相比,该方法只需要两倍的计算成本。通过性别依赖的音素和单词识别测试,比较了Mel LPC分析获得的Mel -倒谱参数与传统LP Mel -倒谱和Mel -频率倒谱coe(cid:14)客户(MFCC)的识别性能。结果表明,Mel-LPC倒频谱的识别精度比传统的LP倒频谱有显著提高(cid:12),对男性说话人的识别精度略高,对女性说话人的识别精度略低于MFCC。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An efficient mel-LPC analysis method for speech recognition
This paper proposes a simple and e(cid:14)cient time domain technique to estimate an all-poll model on a mel-frequency axis (Mel-LPC). This method requires only two-fold computational cost as compared to conventional linear prediction analysis. The recognition performance of mel-cepstral parameters obtained by the Mel LPC analysis is compared with those of conventional LP mel-cepstra and the mel-frequency cepstrum coe(cid:14)cients (MFCC) through gender-dependent phoneme and word recognition tests. The results show that the Mel-LPC cepstrum attains a signi(cid:12)cant improvement in recognition accuracy over conventional LP mel-cepstrum, and gives slightly higher accuracy for male speakersand slightlylower accuracy for female speakersthan MFCC.
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