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2021 | OriginalPaper | Chapter

Voice Conversion Using Spectral Mapping and TD-PSOLA

Authors : Srinivasan Kannan, Pooja. R. Raju, R. Sai Surya Madhav, Shikha Tripathi

Published in: Advances in Computing and Network Communications

Publisher: Springer Singapore

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Abstract

In this paper, we propose a novel approach for a voice conversion system that makes effective use of spectral characteristics and excitation information, to optimally morph voice. This work addresses some key issues that are not adequately addressed in reported literature and achieves a more holistic voice conversion system. This is achieved using a strategic combination of line spectral frequencies (LSFs) to minimize the effects of over smoothing, a neural network for performing nonlinear spectral mapping and time-domain pitch synchronous overlap add to account for the interaction of excitation signal with the vocal tract. Within this proposed system, two different methods of pitch modification have been suggested, and the performance of these is compared with existing models of comparable complexity. The proposed methods have an average LSF performance index of 0.4082 and 0.4008, respectively, which is higher than existing similar work reported.

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Title: Voice Conversion Using Spectral Mapping and TD-PSOLA
Authors: Srinivasan Kannan
Pooja. R. Raju
R. Sai Surya Madhav
Shikha Tripathi
Publisher: Springer Singapore
Book: Advances in Computing and Network Communications
Print ISBN: 978-981-336-986-3

Electronic ISBN: 978-981-336-987-0

Copyright Year: 2021
DOI: https://doi.org/10.1007/978-981-33-6987-0_17

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