---
dataset_info:
  features:
  - name: audio
    dtype: audio
  - name: transcription
    dtype: string
  splits:
  - name: train
    num_bytes: 1275875540.632
    num_examples: 2378
  download_size: 976321234
  dataset_size: 1275875540.632
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
task_categories:
- automatic-speech-recognition
size_categories:
- 1K<n<10K
---


# High quality TTS data for four South African languages - Setswana

### Source - https://openslr.org/32/
### Identifier: SLR32

Summary: Multi-speaker TTS data for four South African languages - Setswana

License: Attribution-ShareAlike 4.0 International (CC BY-SA 4.0)

About this resource:

This data set contains multi-speaker high quality transcribed audio data for four languages of South Africa. The data set consists of wave files, and a TSV file transcribing the audio. In each folder, the file line_index.tsv contains a FileID, which in turn contains the UserID and the Transcription of audio in the file.
The data set has had some quality checks, but there might still be errors.

This data set was collected by as a collaboration between North West University and Google.

If you use this data in publications, please cite it as follows:

```
  @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.