ElizabethMwangi/whisper-large-v3-luganda-nss

Whisper Large V3 — Luganda (Nonstandard Speech)

Fine-tuned versions of openai/whisper-large-v3 for automatic speech recognition of Luganda, trained on nonstandard speech from the CDLI Ugandan Luganda Nonstandard Speech dataset.

Runs

Run	Folder	Decoder Frozen	Augmentation	SpecAugment	Best Checkpoint	Avg WER
Run 1 (v16)	v16-checkpoint-350	Yes (encoder only)	Yes	Off	Step 350	53.4%
Run 2 (v17)	v17-checkpoint-350	No (full model)	No	Off	Step 350	53.3%
Run 3 (v20)	v20-checkpoint-500	No (full model)	No	On	Step 500	53.9%

Preferred model: Run 2 (v17) — best performance on moderate and severe speakers.

Usage

from transformers import pipeline

asr = pipeline(
    "automatic-speech-recognition",
    model="ElizabethMwangi/whisper-large-v3-luganda-nss",
    model_kwargs={"subfolder": "v17-checkpoint-350"}
)
result = asr("audio.wav")
print(result["text"])
\```

## Model Details

- **Base model:** openai/whisper-large-v3
- **Language:** Luganda (`lg`)
- **Task:** Automatic Speech Recognition (ASR)
- **Training data:** cdli/ugandan_luganda_nonstandard_speech_v1.0
- **Language token:** sw (Swahili used as proxy for Luganda)
- **Length limit:** enabled

## Intended Use

This model is intended for transcription of Luganda nonstandard speech, including dysarthric, stuttering, and otherwise atypical speech patterns. It is part of ongoing research into inclusive ASR for low-resource Ugandan languages.

## Limitations

- Optimised for Luganda nonstandard speech; performance on standard Luganda or other languages may vary
- Language token is set to Swahili (`sw`) as a proxy for Luganda

## Citation

If you use this model, please cite the CDLI Ugandan Luganda Nonstandard Speech dataset and this repository.