The Voice Conversion Challenge 2016
收藏DataCite Commons2023-04-27 更新2025-04-17 收录
下载链接:
https://datashare.ed.ac.uk/handle/10283/2211
下载链接
链接失效反馈官方服务:
资源简介:
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. For further information please see the accompanying paper "Interspeech2016_VC_challenge_description.pdf" included in this dataset. See also "The Voice Conversion Challenge, 2016: multidimensional scaling (MDS) listening test results" (DOI: 10.7488/ds/1504).
提供机构:
University of Edinburgh. School of Informatics. Centre for Speech Technology Research
创建时间:
2016-12-05



