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CSTR VCTK
Audio
NLP
|...
License: CC BY 4.0

Overview

This CSTR VCTK Corpus includes speech data uttered by 110 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. All recordings were converted into 16 bits, were downsampled to 48 kHz, and
were manually end-pointed. This corpus was originally 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. This corpus is also
suitable for DNN-based multi-speaker text-to-speech synthesis systems and neural waveform modeling.
Please note while text files containing transcripts of the speech are provided for 109 of the
110 recordings, in the '/txt' folder, the 'p315' text was lost due to a hard disk error.

Data Collection

All speech data was recorded using an identical recording setup: an omni-directional microphone
(DPA 4035) and a small diaphragm condenser microphone with very wide bandwidth (Sennheiser
MKH 800), 96kHz sampling frequency at 24 bits and in a hemi-anechoic chamber of the University
of Edinburgh. (However, two speakers, p280 and p315 had technical issues of the audio recordings
using MKH 800).

Citation

Please use the following citation when referencing the dataset:

@ARTICLE{vctk,
  title={CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit},
  author={Yamagishi, Junichi and Veaux, Christophe and MacDonald, Kirsten.},
  url={https://doi.org/10.7488/ds/2645}
}

License

CC BY 4.0

Data Summary
Type
Audio,
Amount
--
Size
10.94GB
Provided by
CSTR (The Centre for Speech Technology Research)
CSTR is an interdisciplinary research centre linking Informatics and Linguistics and English Language.
| Amount -- | Size 10.94GB
CSTR VCTK
Audio
NLP
License: CC BY 4.0

Overview

This CSTR VCTK Corpus includes speech data uttered by 110 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. All recordings were converted into 16 bits, were downsampled to 48 kHz, and
were manually end-pointed. This corpus was originally 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. This corpus is also
suitable for DNN-based multi-speaker text-to-speech synthesis systems and neural waveform modeling.
Please note while text files containing transcripts of the speech are provided for 109 of the
110 recordings, in the '/txt' folder, the 'p315' text was lost due to a hard disk error.

Data Collection

All speech data was recorded using an identical recording setup: an omni-directional microphone
(DPA 4035) and a small diaphragm condenser microphone with very wide bandwidth (Sennheiser
MKH 800), 96kHz sampling frequency at 24 bits and in a hemi-anechoic chamber of the University
of Edinburgh. (However, two speakers, p280 and p315 had technical issues of the audio recordings
using MKH 800).

Citation

Please use the following citation when referencing the dataset:

@ARTICLE{vctk,
  title={CSTR VCTK Corpus: English Multi-speaker Corpus for CSTR Voice Cloning Toolkit},
  author={Yamagishi, Junichi and Veaux, Christophe and MacDonald, Kirsten.},
  url={https://doi.org/10.7488/ds/2645}
}

License

CC BY 4.0

0
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