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This paper proposes a novel voice conversion method by frequency warping. The frequency warp-ing function is generated based on mapping formants of the source speaker and the target speaker. In addi-tion to frequency warping, fundamental frequency adjustment, spectral envelope equalization, breathiness addition, and duration modification are also used to improve the similarity to the target speaker. The pro-posed voice conversion method needs only a very small amount of training data for generating the warping function, thereby greatly facilitating its application. Systems based on the proposed method were used for the 2007 TC-STAR intra-lingual voice conversion evaluation for English and Spanish and a cross-lingual voice conversion evaluation for Spanish. The evaluation results show that the proposed method can achieve a much better quality of converted speech than other methods as well as a good balance between quality and similarity. The IBM1 system was ranked No. 1 for English evaluation and No. 2 for Spanish evaluation. Evaluation results also show that the proposed method is a convenient and competitive method for cross-lingual voice conversion tasks.
This paper proposes a novel voice conversion method by frequency warping. The frequency warp-ing function is generated based on mapping formants of the source speaker and the target speaker. In addi-tion to frequency warping, fundamental frequency adjustment, spectral envelope equalization, breathiness addition, and duration modification are also used to improve the similarity to the target speaker. The pro-posed voice conversion method needs only a very small amount of training data for generating the warping function, thereby greatly facilitating its application. method were used for the 2007 TC-STAR intra-lingual voice conversion evaluation for English and Spanish and a cross-lingual voice conversion evaluation for Spanish. The evaluation results show that the proposed method can achieve a much better quality of converted speech than other methods as well as a good balance between quality and similarity. The IBM1 system was ranked No. 1 for English eval uation and No. 2 for Spanish evaluation. Evaluation results also show that the proposed method is a convenient and competitive method for cross-lingual voice conversion tasks.