ghananlpcommunity/twi-tts-asr

Ghana Twi Speech Dataset (TTS + ASR)

79,655 synthetic Twi speech samples (88.8 hours) generated with OmniVoice. Designed for both text-to-speech (TTS) and automatic speech recognition (ASR) research on Twi.

Intended use

• TTS / Voice cloning: Use the audio + text pairs directly. The dataset includes diverse voice profiles for building or fine-tuning Twi TTS systems.
• ASR: Use the text transcripts as labels. The audio is natively at 24 kHz — resample to 16 kHz for standard ASR pipelines.

Statistics

Metric	Value
Total samples	79,655
Total duration	88.78 hours (319,599 seconds)
Sample rate	24 kHz (native)
Language	Twi
Unique reference speakers	3158
TTS model	k2-fsa/OmniVoice

Columns

Column	Type	Description
id	string	Unique sample ID (zero-padded)
audio	Audio	24 kHz mono WAV audio
text	string	Twi transcription
duration	float	Duration in seconds
ref_speaker	string	Reference speaker ID used for voice cloning

Data generation

• Texts: Sampled from ghananlpcommunity/pristine-twi-english-parallel-sentences (Twi column)
• Voices: Voice-cloned from 3158 reference speakers across 4 Twi speech corpora (JW, Bible, UNICEF, Finance)
• Method: OmniVoice diffusion TTS with random reference audio selection per sample
• Seed: 42 (for reproducibility)

Loading

from datasets import load_dataset

ds = load_dataset("ghananlpcommunity/twi-tts-asr", split="train")
sample = ds[0]
print(sample["text"])         # Twi transcript
print(sample["duration"])     # seconds
print(sample["ref_speaker"])  # which voice was cloned
# -> plays audio

Resampling to 16 kHz for ASR

import torchaudio

def resample_16k(example):
    wav = example["audio"]["array"]
    sr = example["audio"]["sampling_rate"]
    if sr != 16000:
        wav = torchaudio.functional.resample(wav, sr, 16000)
    example["audio_16k"] = wav
    return example

ds_16k = ds.map(resample_16k)