SUPERSEDED - The Voice Conversion Challenge 2016

THIS VERSION HAS BEEN REPLACED DUE TO SOME OF THE FILES BEING CORRUPTED. PLEASE SEE THE NEW VERSION OF THIS DATASET AT https://doi.org/10.7488/ds/1575 . > The Voice Conversion Challenge (VCC) 2016, one of the special sessions at Interspeech 2016, deals with speaker identity conversion, referred as Voice Conversion (VC). 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 consisting of 162 utterances for training and 54 utterances for evaluation from each of 5 source and 5 target speakers, 17 groups working in VC around the world developed their own VC systems for every combination of the source and target speakers, i.e., 25 systems in total, and generated voice samples converted by the developed systems. The objective of the VCC was to compare various VC techniques on identical training and evaluation speech data. The samples were evaluated in terms of target speaker similarity and naturalness by 200 listeners in a controlled environment. This dataset consists of the participants' VC submissions and the listening test results for naturalness and similarity. See also 'The Voice Conversion Challenge, 2016: multidimensional scaling (MDS) listening test results' (DOI: 10.7488/ds/1504).