华东理工大学学报（自然科学版）2017，Vol.43Issue(4)：546-552,7.DOI:10.14135/j.cnki.1006-3080.2017.04.014
一种基于预测谱偏移的自适应高斯混合模型在语音转换中的应用
An Adaptive Gaussian Mixed Model Based on Predictive Spectral Shift and Its Application in Voice Conversion
沈惠玲 1万永菁1
作者信息
- 1. 华东理工大学信息科学与工程学院,上海 200237
- 折叠
摘要
Abstract
Voice conversion algorithm based on Gaussian mixture model (GMM) may result in the over-smoothing of spectral envelop and the damage of speech feature.By analyzing the relationship between covariance's accuracy and over-smoothed phenomena,this paper proposes an adaptive GMM conversion algorithm based on spectral shift,which uses the weighted average algorithm to predict the converted spectral shift.Both the proposed spectral shift and the GMM are adopted to realize the appropriate converted spectral sequence.Moreover,the spectral shift proportion and GMM correlation are adaptively adjusted by using the spectral parameter.The experiment results show that the proposed algorithm can effectively alleviate the over-smoothing and improve the clearness naturalness and intelligibility of converted voice.关键词
语音转换/高斯混合模型/预测谱偏移/自适应Key words
voice conversion/Gaussian mixed model/predictive spectral shift/adaptive分类
信息技术与安全科学引用本文复制引用
沈惠玲,万永菁..一种基于预测谱偏移的自适应高斯混合模型在语音转换中的应用[J].华东理工大学学报（自然科学版）,2017,43(4):546-552,7.
