whipa-large-cv

whipa-large-cv

Model details

This Whisper-for-IPA (WhIPA) model is a fine-tuned version of openai/whisper-large-v2 on a subset of the CommonVoice11 dataset (1k samples each from Greek, Finnish, Hungarian, Japanese, Maltese, Polish, Tamil) with G2P-based IPA transcriptions. It (6) achieves the following results on the evaluation set:

• Loss: 0.5570
• Lvnshtn: 5.9371
• cer: 0.1709
• cer_norm: 0.1604
• ped: 5.5229
• per: 0.1810
• pfer: 5.7470
• LhPD_(mipa): 2.0216
• wefed: 17.9254
• wefer: 0.5507

Model description

For deployment and description, please refer to https://github.com/jshrdt/whipa.

from transformers import WhisperForConditionalGeneration, WhisperTokenizer, WhisperProcessor

whipa_model = WhisperForConditionalGeneration.from_pretrained("jshrdt/whipa-large-cv")

whipa_model.generation_config.language = "<|ip|>"
whipa_model.generation_config.task = "transcribe"

whipa_tokenizer = WhisperTokenizer.from_pretrained("jshrdt/whipa-large-cv", task="transcribe")
whipa_processor = WhisperProcessor.from_pretrained("jshrdt/whipa-large-cv", task="transcribe")

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How to Get Started with the Model

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Training Details

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