---
language:
- af
- ak
- am
- ar
- fr
- gaa
- ha
- ig
- rw
- nso
- st
- sn
- sw
- tn
- tw
- xh
- yo
- zu
pretty_name: >-
  AfriVox: An African benchmark dataset for Automatic Speech
  Translation and Speech Recognition
---
# AfriVox: An African benchmark dataset for Automatic Speech Translation and Speech Recognition


### Project Overview
This project creates a benchmark dataset for evaluating Automatic Speech Translation and Speech recognition models on African languages. This benchmark dataset covers 18 African languages. See language details below.

### License

[![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa]

This work is licensed under a
[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa].

[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa]

[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/
[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png
[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg




### Usage Instructions
**Accessing the Dataset**: The dataset can be accessed through Hugging Face:
```python
from datasets import load_dataset
afrivox = load_dataset("intronhealth/afrivox")
```

## Afrivox stats

- Dataset size = 18,881
- Total number of languages = 18
- Total number of hours = 64.26


### Duration (hours) per domian:
| domain     | duration (hours)|
|------------|-----------------|
|medical     |35.27            |
|non-medical | 28.99           |

### Gender Distribution
| gender | count  |
|--------|-------:|
| Male   | 8879   |
| Female | 10002  |


### Dataset Summary by Language and Domain
| language      | medical (hrs) | non-medical (hrs) | total_hrs | num_speakers | num_samples |
|---------------|--------:|------------:|----------:|-------------:|------------:|
| afrikaans     |    1.79 |        2.27 |      4.05 |           42 |        1406 |
| akan          |    0.67 |        0.58 |      1.24 |           15 |         411 |
| amharic       |    0.37 |        0.26 |      0.62 |            8 |         214 |
| arabic        |    1.47 |        1.13 |      2.60 |           26 |         799 |
| french        |    0.30 |        0.21 |      0.51 |            9 |         135 |
| ga            |    0.00 |        0.01 |      0.01 |            1 |           5 |
| hausa         |    3.81 |        1.71 |      5.53 |          125 |        1869 |
| igbo          |    1.66 |        1.42 |      3.08 |           37 |         970 |
| kinyarwanda   |    2.80 |        2.20 |      5.00 |           48 |        1172 |
| pedi          |    2.18 |        1.94 |      4.13 |           33 |        1121 |
| sesotho       |    2.56 |        2.11 |      4.68 |           28 |        1356 |
| shona         |    2.81 |        2.18 |      4.99 |           41 |        1114 |
| swahili       |    3.35 |        2.57 |      5.92 |          121 |        1377 |
| tswana        |    2.09 |        3.56 |      5.65 |           51 |        1573 |
| twi           |    0.58 |        0.13 |      0.71 |            4 |         339 |
| xhosa         |    3.31 |        2.70 |      6.01 |           58 |        1799 |
| yoruba        |    1.56 |        1.25 |      2.81 |           78 |         890 |
| zulu          |    3.95 |        2.75 |      6.70 |           73 |        2331 |






### Data column descriptions

- **speaker_id** [string]: speaker id for mapping to the audio file to the speaker
- **audio_path** [string]: path to the audio file
- **transcription** [string]: text transcription of the audio file
- **translation** [string]: text translation of the audio file
- **domain** [string]: domain (medical or non-medical)
- **language** [string]: language of the audio file
- **gender** [string]: gender of the speaker
- **duration** [float]: duration of the audio file in seconds