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Update conformer_ctc.rst

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Mingshuang Luo 2021-10-09 10:15:20 +08:00 committed by GitHub
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docs/source/recipes/librispeech/conformer_ctc.rst
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@ -292,16 +292,16 @@ The commonly used options are:
- ``--method``
This specifies the decoding method. This script support seven decoding methods.
This specifies the decoding method. This script supports 7 decoding methods.
As for ctc decoding, it uses a sentence piece model to convert word pieces to words.
And it needs neither a lexicon nor an n-gram LM.
For example, the following command uses CTC topology for rescoring:
For example, the following command uses CTC topology for decoding:
.. code-block::
$ cd egs/librispeech/ASR
$ ./conformer_ctc/decode.py --method ctc-decoding --max-duration 300 --bucketing-sampler False
$ ./conformer_ctc/decode.py --method ctc-decoding --max-duration 300
And the following command uses attention decoder for rescoring:
@ -319,12 +319,8 @@ The commonly used options are:
It has the same meaning as the one during training. A larger
value may cause OOM.
- ``--bucketing-sampler``
When enabled, the batches will come from buckets of similar duration (saves padding frames).
Here are some results for reference based on CTC decoding when set vocab size as 500:
Here are some results for CTC decoding with a vocab size of 500:
Usage:
@ -335,8 +331,6 @@ Usage:
--epoch 25 \
--avg 1 \
--max-duration 300 \
--bucketing-sampler 0 \
--full-libri 0 \
--exp-dir conformer_ctc/exp \
--lang-dir data/lang_bpe_500 \
--method ctc-decoding