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metadata
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

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

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:

@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