Implementation of computationally efficient real-time voice conversion
Tomoki Toda, Takashi Muramatsu, Hideki Banno · 2012
This paper presents an implementation of real-time processing of statistical voice conversion (VC) based on Gaussian mixture models (GMMs). To develop VC applications for enhancing our human-to-human speech communication, it is essential to implement real-time conversion processing. Moreover, it is useful to reduce computational complexity of the conversion processing for making VC applications available even in limited resources. In this paper, we propose a real-time VC method based on a low-delay conversion algorithm considering dynamic features and a global variance. Moreover, we also propose a computationally efficient VC method based on rapid source feature extraction and diagonalization of full covariance matrices. Some experimental results are presented to show that the proposed methods work reasonably well. Index Terms: voice conversion, real-time processing, lowdelay conversion, computational efficiency