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Depositordc.contributorWard, Pauline
Depositordc.contributorWester, Mirjam
Funderdc.contributor.otherEPSRC - Engineering and Physical Sciences Research Councilen_UK
Data Creatordc.creatorTomoki, Toda
Data Creatordc.creatorChen, Ling-Hui
Data Creatordc.creatorSaito, Daisuke
Data Creatordc.creatorVillavicencio, Fernando
Data Creatordc.creatorWester, Mirjam
Data Creatordc.creatorWu, Zhizheng
Data Creatordc.creatorYamagishi, Junichi
Date Accessioneddc.date.accessioned2016-12-05T14:01:51Z
Date Availabledc.date.available2016-12-05T14:01:51Z
Citationdc.identifier.citationTomoki, Toda; Chen, Ling-Hui; Saito, Daisuke; Villavicencio, Fernando; Wester, Mirjam; Wu, Zhizheng; Yamagishi, Junichi. (2016). The Voice Conversion Challenge 2016, 2016 [dataset]. University of Edinburgh. School of Informatics. Centre for Speech Technology Research. https://doi.org/10.7488/ds/1575.en
Persistent Identifierdc.identifier.urihttp://hdl.handle.net/10283/2211
Persistent Identifierdc.identifier.urihttps://doi.org/10.7488/ds/1575
Dataset Description (abstract)dc.description.abstractThe 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).en_UK
Dataset Description (TOC)dc.description.tableofcontents.wav files in multiple subdirectories, 4 tab-delimited .txt files plus one .xlsx file outlining variables contained in the .txt files.en_UK
Languagedc.language.isoengen_UK
Publisherdc.publisherUniversity of Edinburgh. School of Informatics. Centre for Speech Technology Researchen_UK
xmlui.dri2xhtml.METS-1.0.item-relation-ispartofseriesdc.relation.ispartofserieshttp://datashare.is.ed.ac.uk/handle/10283/2040
Relation (Is Referenced By)dc.relation.isreferencedbyhttps://doi.org/10.21437/Interspeech.2016-1066en
Relation (Is Referenced By)dc.relation.isreferencedbyTomoki Toda, Ling-Hui Chen, Daisuke Saito, Fernando Villavicencio, Mirjam Wester, Zhizheng Wu, and Junichi Yamagishi. The voice conversion challenge 2016. In Proc. Interspeech, 2016. https://doi.org/10.21437/Interspeech.2016-1066.
Supersedesdc.relation.replaceshttp://datashare.is.ed.ac.uk/handle/10283/2042en_UK
Rightsdc.rightsCreative Commons Attribution 4.0 International Public Licenseen
Sourcedc.sourceMysore, Gautham J. "DAPS (Device and Produced Speech) Dataset - A dataset of professional production quality speech and corresponding aligned speech recorded on common consumer devices" https://archive.org/details/daps_dataseten
Subjectdc.subjectvoice conversionen_UK
Subjectdc.subjectspeaker conversionen_UK
Subjectdc.subjectevaluationen_UK
Subject Classificationdc.subject.classificationMathematical and Computer Sciences::Speech and Natural Language Processingen_UK
Titledc.titleThe Voice Conversion Challenge 2016en_UK
Alternative Titledc.title.alternativeVCC 2016en_UK
Typedc.typedataseten_UK

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