Fractal dimension feature for distinguishing between overlapped speech and single-speaker speech

Wei Li, Qianhua He, Yanxiong Li, Xueyuan Zhang, Xiaohui Feng
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Abstract

This paper proposes to distinguish between overlapped speech and single-speaker speech using fractal dimension feature. It is found that the degree of chaos in single-speaker speech frames is lower than that in overlapped speech frames, which indicates that the fractal dimension can be used as a feature to distinguish overlapped speech from single-speaker speech. We carried out experiments for evaluating the effectiveness of fractal dimension. Experimental results show that combining traditional features with fractal dimension feature achieves the highest discrimination rate of 81.0%.
分形维数特征用于区分重叠语音和单说话人语音
本文提出利用分形维数特征来区分重叠语音和单说话人语音。研究发现,单说话人语音帧的混沌程度低于重叠语音帧,这表明分形维数可以作为区分重叠语音和单说话人语音的特征。对分形维数的有效性进行了实验评价。实验结果表明,将传统特征与分形维数特征相结合,识别率最高,达到81.0%。
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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