README.md

---
license: mit
dataset_info:
  features:
  - name: speaker_id
    dtype: string
  - name: age_range
    dtype: string
  - name: gender
    dtype: string
  - name: prompt_set
    dtype: string
  - name: transcript
    dtype: string
  - name: duration
    dtype: float32
  - name: split
    dtype: string
  - name: audio
    dtype: audio
  - name: file_name
    dtype: string
  - name: error
    dtype: string
  splits:
  - name: train
    num_bytes: 3440028114.5242105
    num_examples: 46303
  - name: validation
    num_bytes: 145645851.14104894
    num_examples: 1893
  - name: test
    num_bytes: 124887196.19536817
    num_examples: 1681
  download_size: 3793641295
  dataset_size: 3710561161.8606277
configs:
- config_name: default
  data_files:
  - split: train
    path: data/train-*
  - split: validation
    path: data/validation-*
  - split: test
    path: data/test-*
task_categories:
- automatic-speech-recognition
language:
- en
- tw
---

# Dataset Card for KasaSpeech

## Dataset Description

- **Homepage:** https://huggingface.co/datasets/Kennethdot/Ghana_English-Twi_Code_switching_ASR
- **License:** CC BY 4.0
- **Languages:** English (`en`), Twi/Akan (`tw`), English–Twi code-switching
- **Tasks:** Automatic Speech Recognition (ASR), multilingual speech modeling, code-switching research

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

| 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

```python
from datasets import load_dataset

ds = load_dataset("Kennethdot/Ghana_English-Twi_Code_switching_ASR")

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 standardized 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:

```bibtex
@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