DocumentCode :
2213578
Title :
Duration modelling in voice conversion using artificial neural networks
Author :
Srikanth, Ronanki ; Bajibabu, B. ; Prahallad, Kishore
Author_Institution :
Int. Inst. of Inf. Technol., Hyderabad, India
fYear :
2012
fDate :
11-13 April 2012
Firstpage :
556
Lastpage :
559
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.
Keywords :
neural nets; speaker recognition; speech processing; ANN; artificial neural networks; duration modelling; objective measures; prosody features; source speaker; spectral features; speech signal; speech sounds; subjective measures; target speaker; voice conversion; voice quality; voice transformation; Artificial neural networks; Databases; Feature extraction; Speech; Training; Transforms; Vectors; Artificial Neural Networks; Prosody Modification; Voice Transformation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Systems, Signals and Image Processing (IWSSIP), 2012 19th International Conference on
Conference_Location :
Vienna
ISSN :
2157-8672
Print_ISBN :
978-1-4577-2191-5
Type :
conf
Filename :
6208202
Link To Document :
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