Kennethdot/Ghana_English-Twi_Code-switching_ASR

Dataset Card for KasaSpeech

KasaSpeech is a large-scale English–Twi code-switching speech dataset created to advance speech AI research for low-resource African languages. The dataset contains transcribed speech recordings featuring natural switching between English and Twi, collected from diverse speakers primarily in Ghana.

Dataset Structure

Data Splits

The current version of the dataset shows these statistics

Split	Samples
Train	48,292
Test	1,005
Validation	581
Total	49,878

Data Fields

Field	Type	Description
speaker_id	string	Anonymous speaker identifier
gender	string	Speaker gender
age_group	string	Speaker age group
audio	Audio	Speech recording (48kHz)
transcript	string	Human-annotated transcript
split	string	Dataset split: train / validation / test

Example

from datasets import load_dataset, Audio

ds = load_dataset("Kennethdot/Ghana_English-Twi_Code_switching_ASR")
ds = ds.cast_column('audio', Audio(sampling_rate=16000))

sample = ds["train"][0]
print(sample["transcript"])  # e.g. "Ghanaian Jollof and Nigerian Jollof are both nice, nti gyae saa comparison no."
sample["audio"]                 # {"array": [...], "sampling_rate": 16000}

Data Collection

Speech recordings were voluntarily contributed by speakers and manually transcribed following unified annotation guidelines for English–Twi code-switching speech. Audio was cleaned, validated, and cast to 16kHz mono for speech modeling tasks.

Intended Use

KasaSpeech is intended for:

• Automatic Speech Recognition (ASR) — training and evaluating ASR models on code-switched speech
• Multilingual and code-switching research — studying intra-sentential and inter-sentential switching
• African language technology development — building tools for Twi and Ghanaian English speakers
• Speech representation learning — pre-training and fine-tuning models such as Whisper and wav2vec 2.0

Limitations

• Demographic imbalance may exist across gender and age groups
• Recording quality varies across speakers and environments
• Primarily reflects Ghanaian English–Twi speech patterns and may not generalize to other Twi dialects

Citation

If you use KasaSpeech in your research, please cite:

@dataset{kasaspeech2026,
  title   = {KasaSpeech: An English--Twi Code-Switching Speech Dataset},
  author  = {Dotse, Kenneth},
  year    = {2026},
  url     = {https://huggingface.co/datasets/Kennethdot/Ghana_English-Twi_Code_switching_ASR}
}

Contact

For questions or collaboration, please open a discussion on the dataset page