Cross-language voice conversion based on eigenvoices

[en] This paper presents a novel cross-language voice conversion (VC) method based on eigenvoice conversion (EVC). Cross-language VC is a technique for converting voice quality between two speakers uttering different languages each other. In general, parallel data consisting of utterance pairs of those two speakers are not available. To deal with this problem, we apply EVC to cross-language VC. First, we train an eigenvoice GMM (EV-GMM) using many parallel data sets by a source speaker and many pre-stored other speakers who can utter the same language as the source speaker. And then, the conversion model between the source speaker and a target speaker who cannot utter the source speaker's language is developed by adapting the EV-GMM using a few arbitrary sentences uttered by the target speaker in a different language. The experimental results demonstrate that the proposed method yields significant performance improvements in both speech quality and conversion accuracy for speaker individuality compared with a conventional cross-language VC method based on frame selection.

Disciplines :

Electrical & electronics engineering

Author, co-author :

Charlier, M.

Ohtani, Y.

Toda, T.

Moinet, Alexis ; Université de Mons > Faculté Polytechnique > Information, Signal et Intelligence artificielle

Dutoit, Thierry ; Université de Mons > Faculté Polytechnique > Information, Signal et Intelligence artificielle

Language :

English

Title :

Cross-language voice conversion based on eigenvoices

Publication date :

06 September 2009

Event name :

Interspeech 2009

Event place :

Brighton, United Kingdom

Event date :

2009

Research unit :

F105 - Information, Signal et Intelligence artificielle

Research institute :

R300 - Institut de Recherche en Technologies de l'Information et Sciences de l'Informatique
R450 - Institut NUMEDIART pour les Technologies des Arts Numériques

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since 24 November 2010

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Bibliography

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