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The computation of probabilities in CTC beam search involves the addition and multiplication of very small numbers. To make sure the numerical stability, many other implementations first convert the probabilities into log format, then execute the operation.
In the Deep Speech 2 project, we implement two versions of beam search decoder, computing probability in the original and log form respectively. Currently, we use the the former for which is found to have a bit benefit in efficiency. But we also care about the numerical stability, so we have an independent test to compare the two decoders with the ctc beam search decoder in TensorFlow.
Run test_ctc_beam_search_decoder.py, the outputs look like
When the length of input probability list is limited to several hundreds, the two decoders get almost the same scores and decoding results. Hence we believe that the numerical stability may be not a problem in the decoder right now, but we will be careful about it all the way.
The text was updated successfully, but these errors were encountered:
kuke
changed the title
Thenumerical stability
The numerical stability in ctc beam search decoder
Jun 14, 2017
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The computation of probabilities in CTC beam search involves the addition and multiplication of very small numbers. To make sure the numerical stability, many other implementations first convert the probabilities into log format, then execute the operation.
In the Deep Speech 2 project, we implement two versions of beam search decoder, computing probability in the original and log form respectively. Currently, we use the the former for which is found to have a bit benefit in efficiency. But we also care about the numerical stability, so we have an independent test to compare the two decoders with the ctc beam search decoder in TensorFlow.
Run
test_ctc_beam_search_decoder.py
, the outputs look likeWhen the length of input probability list is limited to several hundreds, the two decoders get almost the same scores and decoding results. Hence we believe that the numerical stability may be not a problem in the decoder right now, but we will be careful about it all the way.
The text was updated successfully, but these errors were encountered: