- Tytuł:
- Voice Conversion Based on Hybrid SVR and GMM
- Autorzy:
-
Song, P.
Jin, Y.
Zhao, L.
Zou, C. - Powiązania:
- https://bibliotekanauki.pl/articles/177748.pdf
- Data publikacji:
- 2012
- Wydawca:
- Polska Akademia Nauk. Czytelnia Czasopism PAN
- Tematy:
-
voice conversion
support vector regression
Gaussian mixture models
F0 prediction
speaker-specific information - Opis:
- A novel VC (voice conversion) method based on hybrid SVR (support vector regression) and GMM (Gaussian mixture model) is presented in the paper, the mapping abilities of SVR and GMM are exploited to map the spectral features of the source speaker to those of target ones. A new strategy of F0 transfor- mation is also presented, the F0s are modeled with spectral features in a joint GMM and predicted from the converted spectral features using the SVR method. Subjective and objective tests are carried out to evaluate the VC performance; experimental results show that the converted speech using the proposed method can obtain a better quality than that using the state-of-the-art GMM method. Meanwhile, a VC method based on non-parallel data is also proposed, the speaker-specific information is investigated us- ing the SVR method and preliminary subjective experiments demonstrate that the proposed method is feasible when a parallel corpus is not available.
- Źródło:
-
Archives of Acoustics; 2012, 37, 2; 143-149
0137-5075 - Pojawia się w:
- Archives of Acoustics
- Dostawca treści:
- Biblioteka Nauki
Artykuł