Isolated word recognition based upon source coding techniques

A. Buzo, Horacio G. Martinez, C. Rivera, A. Jazcilevich
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Abstract

We describe an application of a recently developed speech compression technique to automatic recognition of isolated words (from a given dictionary). The scheme maps sampled speech, from a given word, into a finite codebook (of the same size as the dictionary) using linear predictive coding (LPC) all-pole models and a minimum distortion or nearest neighbor rule between all samples from the given word and the codewords from the codebook. Standard LPC techniques are used to design the codebook, but the final system requires no on-line LPC analysis.
基于源编码技术的孤立词识别
我们描述了最近开发的语音压缩技术在自动识别孤立词(从给定的字典)中的应用。该方案使用线性预测编码(LPC)全极点模型和给定单词的所有样本与码本中的码字之间的最小失真或最近邻规则,将给定单词的采样语音映射到有限码本中(与字典大小相同)。使用标准的LPC技术来设计码本,但最终系统不需要在线LPC分析。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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