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Update online ASR tutorial #2226
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1. Add figure to explain the caching 2. Fix the initialization of stream iterator
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just some nits — looks good
side thought: do you think it'd be helpful to be explicit about how the quality of the transcriptions is as expected partly because the model is trained on librispeech but is used to perform inference on non-librispeech data?
Co-authored-by: hwangjeff <hwangjeff@users.noreply.github.com>
@mthrok has imported this pull request. If you are a Meta employee, you can view this diff on Phabricator. |
How would you phrase it? I gave some thoughts at the very beginning, but if we mention that the sample is out-of-domain data, then the narrative is "it's not that good and the reason is the sample is out-of-domain". So I decided not to mention. |
Summary: https://554729-90321822-gh.circle-artifacts.com/0/docs/tutorials/online_asr_tutorial.html 1. Add figure to explain the caching 2. Fix the initialization of stream iterator Pull Request resolved: pytorch#2226 Reviewed By: carolineechen Differential Revision: D34265971 Pulled By: mthrok fbshipit-source-id: 243301e74c4040f4b8cd111b363e70da60e5dae4
https://554729-90321822-gh.circle-artifacts.com/0/docs/tutorials/online_asr_tutorial.html