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Design LSP Trajectory Model for Speech Recognition

机译:设计LSP轨迹模型

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摘要

Speech signal is the continuous signal which has the characteristics in its own. For recognizing the speech signal, the system must be able to classify and recognize the speech feature. Almost of this system is speaker-independent speech system. This paper presents statistical methods for speech recognition by extracting the features of the speech and analyzing their trajectory. The speech feature has been extracted to Line Spectral Pairs (LSP) coefficients and then uses the statistic model to pattern the trajectory for recognizing the signal. The result shows that the using technique usually works well which the maximum accuracy of recognition is 99.67% at number 1 of male speech and the minimum accuracy of recognition is 82.33% at number 5 of female speech.
机译:语音信号是具有自身特征的连续信号。为了识别语音信号,系统必须能够对语音功能进行分类和识别。几乎这个系统是扬声器 - 独立的语音系统。本文通过提取语音的特征来提取语音识别的统计方法,并分析它们的轨迹。语音特征已经提取到线频谱对(LSP)系数,然后使用统计模型来模式轨迹以识别信号。结果表明,使用技术通常很好地良好的识别准确度为男性语音的1号识别的最高精度为99.67%,识别的最低精度为女性语音的5号识别的最低精度为82.33%。

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