Multidimensional scaling of systems in the Voice Conversion Challenge 2016

Using Multidimensional Scaling for Assessment Economic Development of Regions

Addressing socio-economic development issues are strategic and most important for any country. Multidimensional statistical analysis methods, including comprehensive index assessment, have been successfully used to address this challenge, but they donchr('39')t cover all aspects of development, leaving some gap in the development of multidimensional metrics. The purpose of the study is to const...

Explorer Multidimensional scaling of systems in the Voice Conversion

Using Context-based Statistical Models to Promote the Quality of Voice Conversion Systems

This article aims to examine methods of optimizing GMM-based voice conversion systems performance in which GMM method is introduced as the basic method for improvement of voice conversion systems performance. In the current methods, due to using a single conversion function to convert all speech units and subsequent spectral smoothing arising from statistical averaging, we will observe quality ...

The Voice Conversion Challenge 2016

This paper describes the Voice Conversion Challenge 2016 devised by the authors to better understand different voice conversion (VC) techniques by comparing their performance on a common dataset. The task of the challenge was speaker conversion, i.e., to transform the voice identity of a source speaker into that of a target speaker while preserving the linguistic content. Using a common dataset...

A Novel Efficient Algorithm for Voice Gender Conversion

Realistic Voice Gender Conversion (VGC) requires independent scaling of the glottal (pitch) and vocal tract (formant) related features of the input speech signal. We present a VGC algorithm which has two novel features. Firstly, an efficient frequency scaling algorithm is presented. Secondly, we use this to scale all frequencies in the input signal by the desired formant scaling factor. We then...