A new voice transformation method based on both linear and nonlinear prediction analysis
作者： Ki Seung Lee , Dae Hee Youn , Il Whan Cha
DOI: 10.1109/ICSLP.1996.607876
关键词:
摘要: We describe a voice transformation method which changes the source speaker's acoustic features to those of target speaker. In are divided into two parts, linear and nonlinear parts. Linear parts characterized by LPC cepstrum coefficients obtained from LP analysis. The part, represents excitation signal, is modelled long-delay predictor using neural net. Conversion rules for signal generated average pitch ratio mapping codebook, based on orthogonal vector space conversion. addition, spectral envelope compensation proposed correct distortion. transformed speech listening test shows that makes it possible convert individuality while maintaining high quality.
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