[crakenzak]

according to their blog post[1], MMS achieves ~half the error rate on words, while supporting 11x more languages. pretty impressive.

[1] https://ai.facebook.com/blog/multilingual-model-speech-recog...

[youssefabdelm]

I wonder what the performance is on English specifically.

Edit: Just checked the paper, it seems to be worse[1][2] but feel free to correct me.

I feel like they should've just taken the Whipser architecture, scaled it, and scaled the dataset as they did.

[1] Page: https://i.imgur.com/bq15Tno.png

[2] Paper: https://scontent.fcai19-5.fna.fbcdn.net/v/t39.8562-6/3488279...

[sacred_numbers]

It's worse on English and a lot of other common languages (see Appendix C of the paper). It does better on less common languages like Latvian or Tajik, though.

[hackernewds]

Which implies, Whisper just hasn't focused on those languages? Seems disingenuous to make the claim that the error rate has halved, when it's worse in the apex language

[whimsicalism]

My guess is wav2vec performs better on low resource than whisper.

[93po]

lack of labels on graph axes should be a crime