Fundamentals of speech recognition
Fundamentals of speech recognition
Acoustic characteristics of speaker individuality: control and conversion
Speech Communication - Special issue: voice conversion: state of the art and perspectives
Stochastic modeling of spectral adjustment for high quality pitch modification
ICASSP '00 Proceedings of the Acoustics, Speech, and Signal Processing, 2000. on IEEE International Conference - Volume 02
ICASSP '01 Proceedings of the Acoustics, Speech, and Signal Processing, 200. on IEEE International Conference - Volume 02
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This paper describes an enhanced system for more efficient voice conversion. A weighted LMSE (Least Mean Squared Error) criterion is adopted, instead of conventional LMSE, for the spectral conversion function training. In addition, a short-term pitch contour mapping algorithm together with a new residual codebook formed from pitch contour is presented. Informal listening tests prove that convincing voice conversion is achieved while maintaining high speech quality. Evaluations by objective tests also show that the proposed system reduces speaker individual discrimination compared with the baseline system in LPC based analysis/synthesis framework.