techiaith/commonvoice_18_0_cy_en
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How to use techiaith/whisper-large-v3-ft-commonvoice-cy-en with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("automatic-speech-recognition", model="techiaith/whisper-large-v3-ft-commonvoice-cy-en") # Load model directly
from transformers import AutoProcessor, AutoModelForSpeechSeq2Seq
processor = AutoProcessor.from_pretrained("techiaith/whisper-large-v3-ft-commonvoice-cy-en")
model = AutoModelForSpeechSeq2Seq.from_pretrained("techiaith/whisper-large-v3-ft-commonvoice-cy-en", device_map="auto")This model is a fine-tuned version of openai/whisper-large-v3 on the techiaith/commonvoice_18_0_cy_en dataset. Both the English and Welsh data have been used to fine-tune the whisper model for transcribing both languages as well as improved language detection.
It achieves a success rate of 98.86% for language detection on recordings from a Common Voice bilingual test set
While, it achieves the following WER results for transcribing using the same test set:
N.B. the desired transcript language is not given to the fine-tuned model during testing.
from transformers import pipeline
transcriber = pipeline("automatic-speech-recognition", model="techiaith/whisper-large-v3-ft-cv-cy-en")
result = transcriber(<path or url to soundfile>)
print (result)
{'text': 'Mae hen wlad fy nhadau yn annwyl i mi.'}
Base model
openai/whisper-large-v3