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A novel Chinese continuous speech endpoint detection method based on time domain features of the word structure

机译:一种基于单词结构时域特征的新型中文连续语音终点检测方法

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Based on the time domain features of Chinese words, which are short time peak-valley energy and zero crossing, we propose a novel method for continuous speech endpoint detection. It is simple and easy to use, with high detection rate and low computational complexity. The effectiveness of the method has been verified by experiments performed on some continuous Chinese speech. Experimental results show that 96% successful endpoint detection rate can be reached for "863" speech. We have also found that the endpoint detection rate could be enhanced further if we take measures to overcome the effect of some inherent speech factors such as the speaker's speaking style, speed, coarticulation, stressing or muting.
机译:基于中文单词的时域特征,这是短时间峰值能量和零交叉,我们提出了一种用于连续语音端点检测的新方法。它简单易用,检测率高,计算复杂性低。通过在一些连续的汉语演讲中进行的实验验证了该方法的有效性。实验结果表明,可以达到96%的成功终点检测率为“863”演讲。我们还发现,如果我们采取措施克服扬声器的说话风格,速度,套装,压力或静音等一些固有语音因素的效果,可以进一步增强端点检测率。

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