Alkamal01/suda-hausa-tts
Suda Hausa TTS Dataset High-quality Hausa speech dataset prepared for fine-tuning XTTS-v2 as part of the Suda project — an open-source Hausa voice AI. Dataset Details Property Value Language Hausa (ha) Clips 4,960 Duration ~10 hours Sample rate 22,050 Hz mono WAV Format LJSpeech (metadata.csv + wavs/) Speaker Single speaker (male, Nigerian Hausa) Source BibleTTS Hausa License CC-BY-SA 4.0 Source Derived from BibleTTS… See the full description on the dataset page: https://huggingface.co/datasets/Alkamal01/suda-hausa-tts.
Suda Hausa TTS Dataset
High-quality Hausa speech dataset prepared for fine-tuning XTTS-v2 as part of the Suda project — an open-source Hausa voice AI.
Dataset Details
Source
Derived from BibleTTS Hausa by Meyer et al. (2022):
- Original: 40,603 verses, 86.6 hours, studio-quality 48kHz FLAC, single speaker
- This subset: 4,960 clips (1–30s), resampled from 48kHz → 22,050 Hz mono WAV
Structure
suda-dataset/
├── metadata.csv # pipe-delimited: wavs/file.wav|transcript
└── wavs/
├── suda_0000000.wav
├── suda_0000001.wav
└── ...metadata.csv format (LJSpeech):
wavs/suda_0000000.wav|Zan miƙa hannuna gāba da Yahuda da kuma dukan mazaunan Urushalima.
wavs/suda_0000001.wav|Aka yi shela a duk fāɗin Yahuda da Urushalima.Usage
Load metadata
import pandas as pd
df = pd.read_csv(
"hf://datasets/Alkamal01/suda-hausa-tts/metadata.csv",
sep="|",
header=None,
names=["path", "transcript"],
)
print(df.head())Fine-tune XTTS-v2
from TTS.tts.configs.xtts_config import XttsConfig
from TTS.tts.datasets import load_tts_samples
config = XttsConfig()
config.datasets = [{
"formatter": "ljspeech",
"dataset_name": "suda_hausa",
"path": "/path/to/suda-dataset",
"meta_file_train": "metadata.csv",
"language": "ha",
}]See full training script: train_xtts_hausa.py
Processing
Dataset was prepared using open-source scripts in the OribAI-all repo:
- Streamed BibleTTS Hausa parquet shards from HuggingFace
- Filtered clips to 1–30 seconds
- Resampled 48kHz FLAC → 22,050 Hz mono WAV (
scipy.signal.resample_poly) - Wrote LJSpeech-format
metadata.csv
Citation
If you use this dataset, cite the original BibleTTS paper:
@article{meyer2022bibletts,
title = {BibleTTS: a large, high-fidelity, multilingual, and uniquely African speech corpus},
author = {Meyer, Josh and others},
journal = {arXiv preprint arXiv:2207.03546},
year = {2022}
}Project
Part of Suda — open-source Hausa voice AI built by Keuro Lab.
