An algorithm for voice conversion with limited corpus
An algorithm for voice conversion with limited corpus作者机构：School of Communication Engineering Hangzhou Dianzi University
出 版 物：《Chinese Journal of Acoustics》 (声学学报（英文版）)
年 卷 期：2018年第37卷第3期
页 面：371-384页
核心收录：
基 金：supported by the Natural Science Foundation of China(61201301,61772166) Zhejiang Provincial Natural Science Foundation of China(LY16F010012,LY16F020016)
主 题：DTW An algorithm for voice conversion with limited corpus
摘 要：Under the condition of limited target speaker＇s corpus, this paper proposed an algorithm for voice conversion using unified tensor dictionary with limited corpus. Firstly, parallel speech of N speakers was selected randomly from the speech corpus to build the base of tensor dictionary. And then, after the operation of multi-series dynamic time warping for those chosen speech, N two-dimension basic dictionaries can be generated which constituted the unified tensor dictionary. During the conversion stage, the two dictionaries of source and target speaker were established by linear combination of the N basic dictionaries using the two speakers＇ speech. The experimental results showed that when the number of the basic speaker was 14, our algorithm can obtain the compared performance of the traditional NMF- based method with few target speaker corpus, which greatly facilitate the application of voice conversion system.
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