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CSTR VCTK Corpus
English Multi-speaker Corpus for CSTR Voice Cloning Toolkit
(Version 0.80)
RELEASE August 2012
The Centre for Speech Technology Research
University of Edinburgh
Copyright (c) 2012
Junichi Yamagishi
jyamagis@inf.ed.ac.uk
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Overview
This CSTR VCTK Corpus includes speech data uttered by 109 English
speakers with various accents. Each speaker reads out about 400
sentences, which were selected from a newspaper, the rainbow passage
and an elicitation paragraph used for the speech accent archive.
The newspaper texts were taken from Herald Glasgow, with permission
from Herald & Times Group. Each speaker has a different set of the
newspaper texts selected based a greedy algorithm that increases the
contextual and phonetic coverage.
The rainbow passage and elicitation paragraph are the same for all
speakers. The rainbow passage can be found at International Dialects
of English Archive:
(http://web.ku.edu/~idea/readings/rainbow.htm). The elicitation
paragraph is identical to the one used for the speech accent archive
(http://accent.gmu.edu). The details of the the speech accent archive
can be found at
http://www.ualberta.ca/~aacl2009/PDFs/WeinbergerKunath2009AACL.pdf
All speech data was recorded using an identical recording setup: an
omni-directional microphone (DPA 4035), 96kHz sampling frequency at 24
bits and in a hemi-anechoic chamber of the University of
Edinburgh. All recordings were converted into 16 bits, were downsampled
to 48 kHz based on STPK, and were manually end-pointed.
This corpus is aimed for HMM-based text-to-speech synthesis systems,
especially for speaker-adaptive HMM-based speech synthesis that uses
average voice models trained on multiple speakers and speaker
adaptation technologies.
COPYING
This corpus is licensed under Open Data Commons Attribution License
(ODC-By) v1.0.
http://opendatacommons.org/licenses/by/1.0/
http://opendatacommons.org/licenses/by/summary/
ACKNOWLEDGEMENTS
The CSTR VCTK Corpus was constructed by:
Christophe Veaux (University of Edinburgh)
Junichi Yamagishi (University of Edinburgh)
Kirsten MacDonald
The research leading to these results was partly funded from EPSRC
grants EP/I031022/1 (NST) and EP/J002526/1 (CAF), from the RSE-NSFC
grant (61111130120), and from the JST CREST (uDialogue).
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