GPC method in segment of Chinese continuous sentence

Fan Jing, Liu Huihua, Sun Hai
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Abstract

A new method for recognizing the start and the end of each word in a Chinese continuous sentence is discussed. We define a new recognition characteristic called periodic gradual change (PGC). A continuous speech sentence can be separated into many single words by a combination of the new method of PGC and other characteristics such as zero crossing rate (ZCR), instantaneous swing (E characteristic) and linear predictive coding (LPC) parameter. The recognition rate is improved for continuous speech segmentation by the new method.
汉语连续句分词的GPC方法
讨论了一种汉语连续句中词首和词尾识别的新方法。我们定义了一种新的识别特征,称为周期渐变(PGC)。将新的PGC方法与过零率(ZCR)、瞬时摆动(E特征)和线性预测编码(LPC)参数等特征相结合,可以将一个连续的语音句子分割成多个单字。该方法提高了连续语音分割的识别率。
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