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Is your feature request related to a problem? Please describe.
I've been experimenting with examples/asr/asr_cache_aware_streaming/speech_to_text_cache_aware_streaming_infer.py. One of the things I've noticed is that the "greedy_batched" strategy does not support partial hypotheses. We should add support for this. Right now, streaming of RNN-T models is horrendously slow because we are running the decoder at batch size 1, because we must use the "greedy" strategy when doing streaming. The encoder basically isn't meaningfully contributing to the runtime. The decoder is the main slowdown.
Is your feature request related to a problem? Please describe.
I've been experimenting with
examples/asr/asr_cache_aware_streaming/speech_to_text_cache_aware_streaming_infer.py
. One of the things I've noticed is that the "greedy_batched" strategy does not support partial hypotheses. We should add support for this. Right now, streaming of RNN-T models is horrendously slow because we are running the decoder at batch size 1, because we must use the "greedy" strategy when doing streaming. The encoder basically isn't meaningfully contributing to the runtime. The decoder is the main slowdown.FYI @artbataev .
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