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How to calculate 500ms_context from am_500ms_future_context.arch? #985
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Hey, You need to calculate what is the receptive field in your convolution network, so define which the future tokens / past tokens are used in the computations for particular output frame. I believe in our code it was done automatically, as we define function for conv to compute its receptive field depending on the conv params and then propagate to the next layer. cc @vineelpratap if I am wrong. |
@tlikhomanenko |
Dear @tlikhomanenko Appreciate your contribution of this paper and answering to my question. I'm so surprised with your work and studying your model, am_500ms_future_context.arch. Especially, I'm interested in model diet and model inference speed Here, I want to ask you something. According to your paper, future context 250msec quite as good as 500msec arch. However I can't find it. Where can I find this model or could you provide this? Sincerly Seung Woo |
Hi @airlab-byeol, would you mind explaining clearly how did you come up with the figure? I feel like it is really close to the answer but don't understand why did you use 100 frames as input. Thank you. |
Question
[A clear, concise description of your setup and question]
Thank you for reading my question in advance.
I have a question.
Paper "https://research.fb.com/wp-content/uploads/2020/01/Scaling-up-online-speech-recognition-using-ConvNets.pdf"
and Example, https://github.com/flashlight/wav2letter/tree/master/recipes/streaming_convnets/librispeech
Above paper and example say that am_500ms_future_context.arch, this model has the 500ms future context.. but I don't understand why the model has 500ms_future_context.
Could you explain how the model has 500ms future context using above architecture, am_500ms_future_context.arch ?
Best Regrad
Seung Woo
Additional Context
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