deepdml/openslr-32-hq-SA-languages
SLR32 – High Quality TTS Data for Four South African Languages Identifier: SLR32License: CC BY-SA 4.0Source: https://www.openslr.org/32/ This dataset contains multi-speaker high quality transcribed audio data for four languages of South Africa: Afrikaans (af_za), Sesotho (st_za), Setswana (tn_za) and isiXhosa (xh_za). The dataset consists of WAV files and a TSV file transcribing the audio. In each folder the file line_index.tsv contains a FileID (which in turn encodes the… See the full description on the dataset page: https://huggingface.co/datasets/deepdml/openslr-32-hq-SA-languages.
SLR32 – High Quality TTS Data for Four South African Languages
Identifier: SLR32 License: CC BY-SA 4.0 Source: https://www.openslr.org/32/
Dataset Description
- Homepage: OpenSLR SLR32
This dataset contains multi-speaker high quality transcribed audio data for four languages of South Africa: Afrikaans (af_za), Sesotho (st_za), Setswana (tn_za) and isiXhosa (xh_za).
The dataset consists of WAV files and a TSV file transcribing the audio. In each folder the file line_index.tsv contains a FileID (which in turn encodes the UserID) and the transcription of the corresponding audio file.
The dataset has had some quality checks, but there might still be errors.
It was collected as a collaboration between North West University and Google.
Configs / Splits
Fields
Citation
@inproceedings{van-niekerk-etal-2017,
title = {{Rapid development of TTS corpora for four South African languages}},
author = {Daniel van Niekerk and Charl van Heerden and Marelie Davel and
Neil Kleynhans and Oddur Kjartansson and Martin Jansche and Linne Ha},
booktitle = {Proc. Interspeech 2017},
pages = {2178--2182},
address = {Stockholm, Sweden},
month = aug,
year = {2017},
URL = {http://dx.doi.org/10.21437/Interspeech.2017-1139}
}Copyright 2017 Google, Inc.
