一种鲁棒自适应阈值的语音端点检测方法
Journal of Xidian University (Natural Science)(2015)
Abstract
针对基于特征的语音端点检测方法在低信噪比及非平稳噪声下检测性能急剧下降的问题,提出了一种鲁棒自适应阈值的语音端点检测方法。采用表征较长时段语音谱平坦度的长时段语音谱平坦度特征,并融合Burg谱估计,与其他传统语音特征相比,提高了语音与噪声的区分度;能更准确地反映背景噪声特征,克服了固定阈值适应性较差的缺陷,从而更大程度上提高了检测的准确率。仿真结果表明,该方法在低信噪比及非平稳噪声下,检测准确率更高,说明该方法在低信噪比及非平稳噪声环境下鲁棒性更好。
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Key words
Burg spectrum estimation,nonstationary noise,low signal-to-noise ratio,long-term spectral flatness measure,speech endpoint detection
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