| Summary: | 碩士 === 國立交通大學 === 電信工程系 === 90 === The performance of voice conversion depends on the mapping function with the aim to convert the characteristic features from the source speaker to the target speaker. Previous research is based on vector cookbook mapping, but the converter’s performance is degraded due to the quantization noise. To overcome this limitation, we proposed two mapping functions based on continuous probabilistic models. One is based on a statistical model, and the other is based on a Gaussian mixture model. To save that the training data, we exploit the high correlation of speech characteristic features, and employ the principal component analysis to reduce the dimension of characteristic features. Simulation results indicate that the proposed mapping function helps to enhance the hearing-impaired speech, especially the fricatives and affricates.
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