For better transcription in more languages, Implement Massively Multilingual Speech - Meta's Open Source model with less than half of Whispers error rate

jojojaeger / whisper-streamlit

this master thesis project is based on OpenAI Whisper with the goal to transcibe interviews

https://openai.com/research/whisper

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For better transcription in more languages, Implement Massively Multilingual Speech - Meta's Open Source model with less than half of Whispers error rate #4

Open menelic opened 1 year ago

menelic commented 1 year ago

Because of the error rate viz and above al speaker detection your whisper ui is better for research use than all the others I have tried. Please consider implementing Meta's MMS with speech recognition and generation support for over 1000 languages at a drastically reduced error rate compared to Whisper:

https://github.com/facebookresearch/fairseq/tree/main/examples/mms

https://ai.facebook.com/blog/multilingual-model-speech-recognition/

jojojaeger commented 1 year ago

sounds great, i will try it out!

menelic commented 1 year ago

have you had the chance to check it out?