Modulation spectrum-constrained trajectory training algorithm for GMM-based Voice Conversion

@article{Takamichi2015ModulationST,
  title={Modulation spectrum-constrained trajectory training algorithm for GMM-based Voice Conversion},
  author={Shinnosuke Takamichi and Tomoki Toda and Alan W. Black and Satoshi Nakamura},
  journal={2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2015},
  pages={4859-4863}
}
This paper presents a novel training algorithm for Gaussian Mixture Model (GMM)-based Voice Conversion (VC). One of the advantages of GMM-based VC is computationally efficient conversion processing enabling to achieve real-time VC applications. On the other hand, the quality of the converted speech is still significantly worse than that of natural speech. In order to address this problem while preserving the computationally efficient conversion processing, the proposed training method enables 1… CONTINUE READING
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