metadata
language:
- en
tags:
- whisper
- speech-recognition
- trinidadian-creole
- accent
- asr
license: mit
model-index:
- name: Accento V2.0
results:
- task:
type: automatic-speech-recognition
metrics:
- name: WER
type: wer
value: 19.94
- name: CER
type: cer
value: 10
Accento V2.0 - Trinidadian Creole English ASR
Accento V2.0 is a fine-tuned Whisper Large V3 Turbo model optimized for Trinidadian Creole English.
Performance
- WER: 19.94% (with beam_size=3)
- CER: 10.00%
- 54% better than base Whisper
- 27% better than Accento V1.0
Usage
from accento import AccentoTranscriber
# Auto-downloads from Hugging Face if not found locally
transcriber = AccentoTranscriber(model_path="models/accento-v2.0")
result = transcriber.transcribe("audio.wav")
print(result.text)
Technical Details
- Base: Whisper Large V3 Turbo (809M params)
- Method: LoRA (rank=32, alpha=64)
- Adapters: ~106M parameters
- Training: 179 labeled samples + iterative training + model soups
License
MIT License