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
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