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--- |
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language: |
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- af |
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- ak |
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- am |
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- ar |
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- fr |
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- gaa |
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- ha |
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- ig |
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- rw |
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- nso |
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- st |
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- sn |
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- sw |
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- tn |
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- tw |
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- xh |
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- yo |
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- zu |
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pretty_name: >- |
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AfriVox: An African benchmark dataset for Automatic Speech |
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Translation and Speech Recognition |
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--- |
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# AfriVox: An African benchmark dataset for Automatic Speech Translation and Speech Recognition |
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### Project Overview |
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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. |
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### License |
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[![CC BY-NC-SA 4.0][cc-by-nc-sa-shield]][cc-by-nc-sa] |
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This work is licensed under a |
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[Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License][cc-by-nc-sa]. |
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[![CC BY-NC-SA 4.0][cc-by-nc-sa-image]][cc-by-nc-sa] |
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[cc-by-nc-sa]: http://creativecommons.org/licenses/by-nc-sa/4.0/ |
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[cc-by-nc-sa-image]: https://licensebuttons.net/l/by-nc-sa/4.0/88x31.png |
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[cc-by-nc-sa-shield]: https://img.shields.io/badge/License-CC%20BY--NC--SA%204.0-lightgrey.svg |
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### Usage Instructions |
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**Accessing the Dataset**: The dataset can be accessed through Hugging Face: |
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```python |
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from datasets import load_dataset |
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afrivox = load_dataset("intronhealth/afrivox") |
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``` |
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## Afrivox stats |
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- Dataset size = 18,881 |
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- Total number of languages = 18 |
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- Total number of hours = 64.26 |
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### Duration (hours) per domian: |
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| domain | duration (hours)| |
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|------------|-----------------| |
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|medical |35.27 | |
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|non-medical | 28.99 | |
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### Gender Distribution |
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| gender | count | |
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|--------|-------:| |
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| Male | 8879 | |
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| Female | 10002 | |
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### Dataset Summary by Language and Domain |
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| language | medical (hrs) | non-medical (hrs) | total_hrs | num_speakers | num_samples | |
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|---------------|--------:|------------:|----------:|-------------:|------------:| |
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| afrikaans | 1.79 | 2.27 | 4.05 | 42 | 1406 | |
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| akan | 0.67 | 0.58 | 1.24 | 15 | 411 | |
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| amharic | 0.37 | 0.26 | 0.62 | 8 | 214 | |
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| arabic | 1.47 | 1.13 | 2.60 | 26 | 799 | |
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| french | 0.30 | 0.21 | 0.51 | 9 | 135 | |
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| ga | 0.00 | 0.01 | 0.01 | 1 | 5 | |
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| hausa | 3.81 | 1.71 | 5.53 | 125 | 1869 | |
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| igbo | 1.66 | 1.42 | 3.08 | 37 | 970 | |
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| kinyarwanda | 2.80 | 2.20 | 5.00 | 48 | 1172 | |
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| pedi | 2.18 | 1.94 | 4.13 | 33 | 1121 | |
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| sesotho | 2.56 | 2.11 | 4.68 | 28 | 1356 | |
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| shona | 2.81 | 2.18 | 4.99 | 41 | 1114 | |
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| swahili | 3.35 | 2.57 | 5.92 | 121 | 1377 | |
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| tswana | 2.09 | 3.56 | 5.65 | 51 | 1573 | |
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| twi | 0.58 | 0.13 | 0.71 | 4 | 339 | |
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| xhosa | 3.31 | 2.70 | 6.01 | 58 | 1799 | |
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| yoruba | 1.56 | 1.25 | 2.81 | 78 | 890 | |
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| zulu | 3.95 | 2.75 | 6.70 | 73 | 2331 | |
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### Data column descriptions |
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- **speaker_id** [string]: speaker id for mapping to the audio file to the speaker |
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- **audio_path** [string]: path to the audio file |
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- **transcription** [string]: text transcription of the audio file |
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- **translation** [string]: text translation of the audio file |
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- **domain** [string]: domain (medical or non-medical) |
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- **language** [string]: language of the audio file |
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- **gender** [string]: gender of the speaker |
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- **duration** [float]: duration of the audio file in seconds |
