sapinsapin/pld
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How to use sapinsapin/whisper-small-pld-bcl with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="sapinsapin/whisper-small-pld-bcl") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("sapinsapin/whisper-small-pld-bcl")
model = AutoModelForSpeechSeq2Seq.from_pretrained("sapinsapin/whisper-small-pld-bcl", device_map="auto")openai/whisper-small finetuned on
sapinsapin/pld.
Extended run: trained to convergence on the bcl portion of PLD read speech, selected on held-out CER. WER/CER are lowercased on the held-out split; CER is the model-selection metric because Philippine-language orthography varies at the word level.
| metric | value |
|---|---|
| cer | 0.0558 |
| wer | 0.1791 |
Trained with finetune_asr.py from the
halohalo pipeline; the dataset
adapter normalizes each corpus to (audio@16k, text, speaker_id) so corpora
are swappable with a --dataset flag.
Base model
openai/whisper-small