Datasets:
|
Download README.md from suleiman2003/afri-temp-data2: direct link, hf CLI and curl.
- Browser
- Download file 1.21 kB
-
https://huggingface.co/datasets/suleiman2003/afri-temp-data2/resolve/main/README.md
- Command line
-
hf download hf://datasets/suleiman2003/afri-temp-data2/README.md
-
curl -L -o README.md https://huggingface.co/datasets/suleiman2003/afri-temp-data2/resolve/main/README.md
1.21 kB
metadata
language:
- ha
license: cc-by-4.0
task_categories:
- automatic-speech-recognition
tags:
- audio
- speech
- hausa
- african-voices
- asr
pretty_name: AfricanVoices Hausa Train
size_categories:
- 10K<n<100K
AfricanVoices Hausa — Train Split
Hausa speech dataset from AfricanVoices.io, uploaded in
Hugging Face audiofolder format.
Usage
from datasets import load_dataset
ds = load_dataset("suleiman2003/afri-temp-data2", split="train")
print(ds[0])
# {{'audio': Audio(...), 'transcript': '...', 'gender': '...', ...}}
Dataset Structure
Each sample contains:
| Field | Description |
|---|---|
audio |
FLAC audio file (auto-loaded by HF) |
transcript |
Hausa text transcription |
speaker_id |
Speaker identifier |
gender |
Speaker gender (m/f) |
age_group |
Speaker age bracket |
education |
Education level |
duration |
Audio duration (seconds) |
language |
Language code |
snr |
Signal-to-noise ratio |
domain |
Topic domain (ev/ag/he/bu) |
Source
- Platform: AfricanVoices.io
- Organization: Data Science Nigeria
- Supported by: Gates Foundation