By Topic

A new voice transformation method based on both linear and nonlinear prediction analysis

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Ki Seung Lee ; Dept. of Electron. Eng., Yonsei Univ., Seoul, South Korea ; Dae Hee Youn ; Il Whan Cha

We describe a voice transformation method which changes the source speaker's acoustic features to those of a target speaker. In the method acoustic features are divided into two parts, linear and nonlinear parts. Linear parts are characterized by LPC cepstrum coefficients which are obtained from LP analysis. The nonlinear part, which represents the excitation signal, is modelled by the long-delay nonlinear predictor using a neural net. Conversion rules for the excitation signal are generated by the average pitch ratio and the mapping codebook, and those for LPC cepstrum coefficients are based on the orthogonal vector space conversion. In addition, the spectral envelope compensation is proposed to correct spectral distortion. In the transformed speech a listening test shows that the proposed method makes it possible to convert speaker's individuality while maintaining high quality

Published in:

Spoken Language, 1996. ICSLP 96. Proceedings., Fourth International Conference on  (Volume:3 )

Date of Conference:

3-6 Oct 1996