Exemplar-based unit selection for voice conversion utilizing temporal information
Zhizheng Wu, Tuomas I. Virtanen, Tomi Kinnunen, Eng Siong Chng, Haizhou Li · 2013
Although temporal information of speech has been shown to play an important role in perception, most of the voice conver-sion approaches assume the speech frames are independent of each other, thereby ignoring the temporal information. In this study, we improve conventional unit selection approach by us-ing exemplars which span multiple frames as base units, and also take temporal information constraint into voice conver-sion by using overlapping frames to generate speech parame-ters. This approach thus provides more stable concatenation cost and avoids discontinuity problem in conventional unit se-lection approach. The proposed method also keeps away from the over-smoothing problem in the mainstream joint density Gaussian mixture model (JD-GMM) based conversion method by directly using target speaker’s training data for synthesizing the converted speech. Both objective and subjective evaluations indicate that our proposed method outperforms JD-GMM and conventional unit selection methods. Index Terms: Voice conversion, unit selection, multi-frame ex-emplar, temporal information