基于连续相关特征的多间距跟踪和混合DBNS/HMM模型

Jie Lin, Gen Zhang, Bo Fu, Yujie Hao
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引用次数: 2

摘要

本文提出了一种新的混合语音信号中多髓的跟踪方法。在该方法中,我们采用了一种新的连续相关特征来计算基音模型。该特征不仅表示了谐波性,还包含了谱连续性信息,从而提高了多音高估计的精度。利用DBNs和HMM混合模型构建基音模型,确定基音状态,搜索最佳基音状态序列。在混合语音数据上对该方法进行了评价,结果证明了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multipitch tracking with continuous correlation feature and hybrid DBNS/HMM model
This paper proposed a new approach used for tracking multi-pith within one mixture speech signal. In this method, we employed a novel continuous correlation feature for calculating pitch model. This feature not only represents the harmonicity but also includes the information of spectral continuity, and hence improving the accuracy of the multi-pitch estimate. A DBNs and HMM hybrid model was further utilized to construct pitch models for determining pitch states and search for the best pitch state sequence. The new approach has been evaluated on mixture speech data and the results demonstrated its efficiency.
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