Non-Linear Pitch Modification in Voice Conversion using Artificial Neural Networks
2013 (English)In: Advances in nonlinear speech processing: 6th International Conference, NOLISP 2013, Mons, Belgium, June 19-21, 2013 : proceedings, Springer Berlin/Heidelberg, 2013, 97-103 p.Conference paper (Refereed)
Majority of the current voice conversion methods do not focus on the modelling local variations of pitch contour, but only on linear modification of the pitch values, based on means and standard deviations. However, a significant amount of speaker related information is also present in pitch contour. In this paper we propose a non-linear pitch modification method for mapping the pitch contours of the source speaker according to the target speaker pitch contours. This work is done within the framework of Artificial Neural Networks (ANNs) based voice conversion. The pitch contours are represented with Discrete Cosine Transform (DCT) coefficients at the segmental level. The results evaluated using subjective and objective measures confirm that the proposed method performed better in mimicking the target speaker's speaking style when compared to the linear modification method.
Place, publisher, year, edition, pages
Springer Berlin/Heidelberg, 2013. 97-103 p.
, Lecture Notes in Computer Science, ISSN 0302-9743 ; 7911
Discrete cosine transform coefficients, Local variations, Modification methods, Pitch modification, Speaking styles, Standard deviation, Subjective and objective measures, Voice conversion
Computer Science Language Technology (Computational Linguistics)
IdentifiersURN: urn:nbn:se:kth:diva-137386DOI: 10.1007/978-3-642-38847-7-13ScopusID: 2-s2.0-84888246669ISBN: 978-364238846-0OAI: oai:DiVA.org:kth-137386DiVA: diva2:678924
6th International Conference on Advances in Nonlinear Speech Processing, NOLISP 2013; Mons; Belgium; 19 June 2013 through 21 June 2013
QC 201401162013-12-132013-12-132014-01-16Bibliographically approved