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Is it safe to assume that the end time for the token is the start time of the next token? It wouldn't be accurate if there's some silence between words unless the aligner can predict blank tokens. Can this be achieved?
As for the confidences, I've thought about estimating it from log_probs like here #1092
I've tried generating alignments for a
pruned_transducer_stateless7
model using https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/pruned_transducer_stateless7/compute_ali.py. Looking at the output cuts I can only find the start times for tokens/words. Is there a way to get the duration and confidence info too?The text was updated successfully, but these errors were encountered: