---
license: cc-by-nc-sa-4.0
task_categories:
- automatic-speech-recognition
language:
- en
tags:
- africa
- parliamentary
- conversational
- noisy
pretty_name: AfriSpeech-Parliament
dataset_info:
  size: 35.86h
  samples: 8068
---

# AfriSpeech-Parliament: Transcribed Parliamentary Sessions from Four African Nations

[![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  

---

### Overview

**AfriSpeech-Parliament** is a 35.86-hour dataset of transcribed parliamentary sessions from Nigeria, Ghana, South Africa, and Kenya. Sourced from their respective official YouTube channels, each sample is a 16-second audio chunk with corresponding manual transcription. The data reflects natural, conversational speech with background noise, overlapping speakers, and crosstalk — capturing the realistic complexity of parliamentary sessions. This dataset is a test-only dataset that can be used to evaluate the robustness of ASR models to noisy, multi-speaker, real-world African-accented conversational speech.

Each sample includes:

- `file_name`: Audio file path  
- `transcript`: Full transcription 
- `country`: One of `GH`, `KE`, `ZA`, or `NG`  
- `accent`: Assigned based on country of parliament session
- `duration`: Duration in seconds (always 16.0s)  
- `age_group`: Annotator's age group  

### Dataset Summary

| Country | No. of Samples |
|---------|---------|
| Kenya   | 3,892   |
| Nigeria | 1,818   |
| South Africa | 1,805 |
| Ghana   | 553     |
| **Total**  | **8,068**   |

- **Total duration**: 35.86 hours  
- **Sample duration**: 16 seconds (for all samples)  
- **Sample rate**: 16kHz, monochannel  
- **Format**: `.wav` audio with plain-text transcription  

### Data Split

This is a **test-only** dataset and does not include train/dev splits.

### How to Load the Dataset

```python
from datasets import load_dataset

dataset = load_dataset("intronhealth/afrispeech-parliament")