mirrors/icefall
1
0
Fork 0
mirror of https://github.com/k2-fsa/icefall.git synced 2025-08-09 01:52:41 +00:00
Code Issues Packages Projects Releases Wiki Activity

deploy: 3a1ce5963b67413b5d274895a1156e20dc30c3be

Browse Source
This commit is contained in:
marcoyang1998 2023-08-29 08:46:37 +00:00
parent aba0aa17b9
commit 5633b5d16e
7 changed files with 25 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

5
_sources/decoding-with-langugage-models/LODR.rst.txt
View File

@ -71,9 +71,12 @@ As the initial step, let's download the pre-trained model.
.. code-block:: bash .. code-block:: bash
$ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29 $ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
$ pushd icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp $ cd icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp
$ git lfs pull --include "pretrained.pt" $ git lfs pull --include "pretrained.pt"
$ ln -s pretrained.pt epoch-99.pt # create a symbolic link so that the checkpoint can be loaded $ ln -s pretrained.pt epoch-99.pt # create a symbolic link so that the checkpoint can be loaded
$ cd ../data/lang_bpe_500
$ git lfs pull --include bpe.model
$ cd ../../..
To test the model, let's have a look at the decoding results **without** using LM. This can be done via the following command: To test the model, let's have a look at the decoding results **without** using LM. This can be done via the following command:

5
_sources/decoding-with-langugage-models/rescoring.rst.txt
View File

@ -34,9 +34,12 @@ As the initial step, let's download the pre-trained model.
.. code-block:: bash .. code-block:: bash
$ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29 $ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
$ pushd icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp $ cd icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp
$ git lfs pull --include "pretrained.pt" $ git lfs pull --include "pretrained.pt"
$ ln -s pretrained.pt epoch-99.pt # create a symbolic link so that the checkpoint can be loaded $ ln -s pretrained.pt epoch-99.pt # create a symbolic link so that the checkpoint can be loaded
$ cd ../data/lang_bpe_500
$ git lfs pull --include bpe.model
$ cd ../../..
As usual, we first test the model's performance without external LM. This can be done via the following command: As usual, we first test the model's performance without external LM. This can be done via the following command:

5
_sources/decoding-with-langugage-models/shallow-fusion.rst.txt
View File

@ -32,9 +32,12 @@ As the initial step, let's download the pre-trained model.
.. code-block:: bash .. code-block:: bash
$ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29 $ GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
$ pushd icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp $ cd icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp
$ git lfs pull --include "pretrained.pt" $ git lfs pull --include "pretrained.pt"
$ ln -s pretrained.pt epoch-99.pt # create a symbolic link so that the checkpoint can be loaded $ ln -s pretrained.pt epoch-99.pt # create a symbolic link so that the checkpoint can be loaded
$ cd ../data/lang_bpe_500
$ git lfs pull --include bpe.model
$ cd ../../..
To test the model, let's have a look at the decoding results without using LM. This can be done via the following command: To test the model, let's have a look at the decoding results without using LM. This can be done via the following command:

5
decoding-with-langugage-models/LODR.html
View File

@ -146,9 +146,12 @@ If you want to train your model from scratch, please have a look at <a class="re
The testing scenario here is intra-domain (we decode the model trained on <a class="reference external" href="https://www.openslr.org/12">LibriSpeech</a> on <a class="reference external" href="https://www.openslr.org/12">LibriSpeech</a> testing sets).</p> The testing scenario here is intra-domain (we decode the model trained on <a class="reference external" href="https://www.openslr.org/12">LibriSpeech</a> on <a class="reference external" href="https://www.openslr.org/12">LibriSpeech</a> testing sets).</p>
<p>As the initial step, let’s download the pre-trained model.</p> <p>As the initial step, let’s download the pre-trained model.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nv">GIT_LFS_SKIP_SMUDGE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>git<span class="w"> </span>clone<span class="w"> </span>https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nv">GIT_LFS_SKIP_SMUDGE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>git<span class="w"> </span>clone<span class="w"> </span>https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
$<span class="w"> </span><span class="nb">pushd</span><span class="w"> </span>icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp $<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp
$<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span><span class="s2">&quot;pretrained.pt&quot;</span> $<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span><span class="s2">&quot;pretrained.pt&quot;</span>
$<span class="w"> </span>ln<span class="w"> </span>-s<span class="w"> </span>pretrained.pt<span class="w"> </span>epoch-99.pt<span class="w"> </span><span class="c1"># create a symbolic link so that the checkpoint can be loaded</span> $<span class="w"> </span>ln<span class="w"> </span>-s<span class="w"> </span>pretrained.pt<span class="w"> </span>epoch-99.pt<span class="w"> </span><span class="c1"># create a symbolic link so that the checkpoint can be loaded</span>
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>../data/lang_bpe_500
$<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span>bpe.model
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>../../..
</pre></div> </pre></div>
</div> </div>
<p>To test the model, let’s have a look at the decoding results <strong>without</strong> using LM. This can be done via the following command:</p> <p>To test the model, let’s have a look at the decoding results <strong>without</strong> using LM. This can be done via the following command:</p>

5
decoding-with-langugage-models/rescoring.html
View File

@ -118,9 +118,12 @@ to any other domains (e.g <a class="reference external" href="https://github.com
If you want to train your model from scratch, please have a look at <a class="reference internal" href="../recipes/Non-streaming-ASR/librispeech/pruned_transducer_stateless.html#non-streaming-librispeech-pruned-transducer-stateless"><span class="std std-ref">Pruned transducer statelessX</span></a>.</p> If you want to train your model from scratch, please have a look at <a class="reference internal" href="../recipes/Non-streaming-ASR/librispeech/pruned_transducer_stateless.html#non-streaming-librispeech-pruned-transducer-stateless"><span class="std std-ref">Pruned transducer statelessX</span></a>.</p>
<p>As the initial step, let’s download the pre-trained model.</p> <p>As the initial step, let’s download the pre-trained model.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nv">GIT_LFS_SKIP_SMUDGE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>git<span class="w"> </span>clone<span class="w"> </span>https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nv">GIT_LFS_SKIP_SMUDGE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>git<span class="w"> </span>clone<span class="w"> </span>https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
$<span class="w"> </span><span class="nb">pushd</span><span class="w"> </span>icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp $<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp
$<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span><span class="s2">&quot;pretrained.pt&quot;</span> $<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span><span class="s2">&quot;pretrained.pt&quot;</span>
$<span class="w"> </span>ln<span class="w"> </span>-s<span class="w"> </span>pretrained.pt<span class="w"> </span>epoch-99.pt<span class="w"> </span><span class="c1"># create a symbolic link so that the checkpoint can be loaded</span> $<span class="w"> </span>ln<span class="w"> </span>-s<span class="w"> </span>pretrained.pt<span class="w"> </span>epoch-99.pt<span class="w"> </span><span class="c1"># create a symbolic link so that the checkpoint can be loaded</span>
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>../data/lang_bpe_500
$<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span>bpe.model
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>../../..
</pre></div> </pre></div>
</div> </div>
<p>As usual, we first test the model’s performance without external LM. This can be done via the following command:</p> <p>As usual, we first test the model’s performance without external LM. This can be done via the following command:</p>

5
decoding-with-langugage-models/shallow-fusion.html
View File

@ -117,9 +117,12 @@ to any other domains (e.g <a class="reference external" href="https://github.com
If you want to train your model from scratch, please have a look at <a class="reference internal" href="../recipes/Non-streaming-ASR/librispeech/pruned_transducer_stateless.html#non-streaming-librispeech-pruned-transducer-stateless"><span class="std std-ref">Pruned transducer statelessX</span></a>.</p> If you want to train your model from scratch, please have a look at <a class="reference internal" href="../recipes/Non-streaming-ASR/librispeech/pruned_transducer_stateless.html#non-streaming-librispeech-pruned-transducer-stateless"><span class="std std-ref">Pruned transducer statelessX</span></a>.</p>
<p>As the initial step, let’s download the pre-trained model.</p> <p>As the initial step, let’s download the pre-trained model.</p>
<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nv">GIT_LFS_SKIP_SMUDGE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>git<span class="w"> </span>clone<span class="w"> </span>https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29 <div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>$<span class="w"> </span><span class="nv">GIT_LFS_SKIP_SMUDGE</span><span class="o">=</span><span class="m">1</span><span class="w"> </span>git<span class="w"> </span>clone<span class="w"> </span>https://huggingface.co/Zengwei/icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29
$<span class="w"> </span><span class="nb">pushd</span><span class="w"> </span>icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp $<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>icefall-asr-librispeech-pruned-transducer-stateless7-streaming-2022-12-29/exp
$<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span><span class="s2">&quot;pretrained.pt&quot;</span> $<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span><span class="s2">&quot;pretrained.pt&quot;</span>
$<span class="w"> </span>ln<span class="w"> </span>-s<span class="w"> </span>pretrained.pt<span class="w"> </span>epoch-99.pt<span class="w"> </span><span class="c1"># create a symbolic link so that the checkpoint can be loaded</span> $<span class="w"> </span>ln<span class="w"> </span>-s<span class="w"> </span>pretrained.pt<span class="w"> </span>epoch-99.pt<span class="w"> </span><span class="c1"># create a symbolic link so that the checkpoint can be loaded</span>
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>../data/lang_bpe_500
$<span class="w"> </span>git<span class="w"> </span>lfs<span class="w"> </span>pull<span class="w"> </span>--include<span class="w"> </span>bpe.model
$<span class="w"> </span><span class="nb">cd</span><span class="w"> </span>../../..
</pre></div> </pre></div>
</div> </div>
<p>To test the model, let’s have a look at the decoding results without using LM. This can be done via the following command:</p> <p>To test the model, let’s have a look at the decoding results without using LM. This can be done via the following command:</p>

2
searchindex.js
View File

File diff suppressed because one or more lines are too long