@@ -303,7 +303,7 @@ The commonly used options are:
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- ``--lattice-score-scale ``
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- It is used to scaled down lattice scores so that we can more unique
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+ It is used to scale down lattice scores so that there are more unique
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paths for rescoring.
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- ``--max-duration ``
@@ -314,7 +314,7 @@ The commonly used options are:
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Pre-trained Model
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-----------------
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- We have uploaded the pre-trained model to
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+ We have uploaded a pre-trained model to
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`<https://huggingface.co/pkufool/icefall_asr_librispeech_conformer_ctc >`_.
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We describe how to use the pre-trained model to transcribe a sound file or
@@ -324,7 +324,7 @@ Install kaldifeat
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~~~~~~~~~~~~~~~~~
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`kaldifeat <https://github.com/csukuangfj/kaldifeat >`_ is used to
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- extract features for a single sound file or multiple soundfiles
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+ extract features for a single sound file or multiple sound files
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at the same time.
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Please refer to `<https://github.com/csukuangfj/kaldifeat >`_ for installation.
@@ -397,7 +397,7 @@ After downloading, you will have the following files:
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- ` ` data/lm/G_4_gram.pt` `
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- It is a 4-gram LM, useful for LM rescoring.
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+ It is a 4-gram LM, used for n-gram LM rescoring.
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- ` ` exp/pretrained.pt` `
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@@ -556,7 +556,7 @@ Its output is:
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HLG decoding + LM rescoring + attention decoder rescoring
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^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
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- It uses an n-gram LM to rescore the decoding lattice, extracts
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+ It uses an n-gram LM to rescore the decoding lattice, extracts
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n paths from the rescored lattice, recores the extracted paths with
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an attention decoder. The path with the highest score is the decoding result.
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