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Duration Modelling in Voice Conversion Using Artificial Neural Networks
Research Area: Speech Synthesis Year: 2012
Type of Publication: In Proceedings  
Authors: Ronanki Srikanth, Bajibabu Bollepalli, Kishore S. Prahallad  
Book title: IWSSIP-2012
Address: Vienna, Austria
Month: 11-13, April
   
Abstract:
Voice conversion aims at transforming the characteristics of a speech signal uttered by a source speaker in such a way that the transformed speech sounds like the target speaker. Such a conversion requires transformation of spectral and prosody features. In this paper, we propose a technique for duration transformation of source speaker to that of a target speaker. This work is done in the framework of Artificial neural networks based voice conversion. The results are evaluated using subjective and objective measures confirm that incorporating durational modification to voice transformation improves the voice quality and has the characteristics of target speaker.
   

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