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<li class="toctree-l3"><a class="reference internal" href="#data-preparation">Data Preparation</a></li>
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<li class="toctree-l3"><a class="reference internal" href="#training">Training</a></li>
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<section id="how-to-create-a-recipe">
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<h1>How to create a recipe<a class="headerlink" href="#how-to-create-a-recipe" title="Permalink to this heading"></a></h1>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>Please read <a class="reference internal" href="code-style.html#follow-the-code-style"><span class="std std-ref">Follow the code style</span></a> to adjust your code style.</p>
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</div>
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<div class="admonition caution">
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<p class="admonition-title">Caution</p>
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<p><code class="docutils literal notranslate"><span class="pre">icefall</span></code> is designed to be as Pythonic as possible. Please use
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Python in your recipe if possible.</p>
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</div>
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<section id="data-preparation">
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<h2>Data Preparation<a class="headerlink" href="#data-preparation" title="Permalink to this heading"></a></h2>
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<p>We recommend you to prepare your training/test/validate dataset
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with <a class="reference external" href="https://github.com/lhotse-speech/lhotse">lhotse</a>.</p>
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<p>Please refer to <a class="reference external" href="https://lhotse.readthedocs.io/en/latest/index.html">https://lhotse.readthedocs.io/en/latest/index.html</a>
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for how to create a recipe in <code class="docutils literal notranslate"><span class="pre">lhotse</span></code>.</p>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>The <code class="docutils literal notranslate"><span class="pre">yesno</span></code> recipe in <code class="docutils literal notranslate"><span class="pre">lhotse</span></code> is a very good example.</p>
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<p>Please refer to <a class="reference external" href="https://github.com/lhotse-speech/lhotse/pull/380">https://github.com/lhotse-speech/lhotse/pull/380</a>,
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which shows how to add a new recipe to <code class="docutils literal notranslate"><span class="pre">lhotse</span></code>.</p>
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</div>
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<p>Suppose you would like to add a recipe for a dataset named <code class="docutils literal notranslate"><span class="pre">foo</span></code>.
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You can do the following:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ cd egs
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$ mkdir -p foo/ASR
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$ cd foo/ASR
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$ touch prepare.sh
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$ chmod +x prepare.sh
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</pre></div>
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</div>
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<p>If your dataset is very simple, please follow
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<a class="reference external" href="https://github.com/k2-fsa/icefall/blob/master/egs/yesno/ASR/prepare.sh">egs/yesno/ASR/prepare.sh</a>
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to write your own <code class="docutils literal notranslate"><span class="pre">prepare.sh</span></code>.
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Otherwise, please refer to
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<a class="reference external" href="https://github.com/k2-fsa/icefall/blob/master/egs/yesno/ASR/prepare.sh">egs/librispeech/ASR/prepare.sh</a>
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to prepare your data.</p>
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</section>
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<section id="training">
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<h2>Training<a class="headerlink" href="#training" title="Permalink to this heading"></a></h2>
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<p>Assume you have a fancy model, called <code class="docutils literal notranslate"><span class="pre">bar</span></code> for the <code class="docutils literal notranslate"><span class="pre">foo</span></code> recipe, you can
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organize your files in the following way:</p>
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<div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ cd egs/foo/ASR
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$ mkdir bar
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$ cd bar
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$ touch README.md model.py train.py decode.py asr_datamodule.py pretrained.py
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</pre></div>
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</div>
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<p>For instance , the <code class="docutils literal notranslate"><span class="pre">yesno</span></code> recipe has a <code class="docutils literal notranslate"><span class="pre">tdnn</span></code> model and its directory structure
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looks like the following:</p>
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<div class="highlight-bash notranslate"><div class="highlight"><pre><span></span>egs/yesno/ASR/tdnn/
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<span class="p">|</span>--<span class="w"> </span>README.md
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<span class="p">|</span>--<span class="w"> </span>asr_datamodule.py
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<span class="p">|</span>--<span class="w"> </span>decode.py
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<span class="p">|</span>--<span class="w"> </span>model.py
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<span class="p">|</span>--<span class="w"> </span>pretrained.py
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<span class="sb">`</span>--<span class="w"> </span>train.py
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</pre></div>
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</div>
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<p><strong>File description</strong>:</p>
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<blockquote>
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<div><ul>
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<li><p><code class="docutils literal notranslate"><span class="pre">README.md</span></code></p>
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<p>It contains information of this recipe, e.g., how to run it, what the WER is, etc.</p>
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</li>
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<li><p><code class="docutils literal notranslate"><span class="pre">asr_datamodule.py</span></code></p>
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<p>It provides code to create PyTorch dataloaders with train/test/validation dataset.</p>
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</li>
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<li><p><code class="docutils literal notranslate"><span class="pre">decode.py</span></code></p>
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<p>It takes as inputs the checkpoints saved during the training stage to decode the test
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dataset(s).</p>
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</li>
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<li><p><code class="docutils literal notranslate"><span class="pre">model.py</span></code></p>
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<p>It contains the definition of your fancy neural network model.</p>
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</li>
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<li><p><code class="docutils literal notranslate"><span class="pre">pretrained.py</span></code></p>
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<p>We can use this script to do inference with a pre-trained model.</p>
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</li>
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<li><p><code class="docutils literal notranslate"><span class="pre">train.py</span></code></p>
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<p>It contains training code.</p>
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</li>
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</ul>
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</div></blockquote>
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<div class="admonition hint">
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<p class="admonition-title">Hint</p>
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<p>Please take a look at</p>
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<blockquote>
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<div><ul class="simple">
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<li><p><a class="reference external" href="https://github.com/k2-fsa/icefall/tree/master/egs/yesno/ASR/tdnn">egs/yesno/tdnn</a></p></li>
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<li><p><a class="reference external" href="https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/tdnn_lstm_ctc">egs/librispeech/tdnn_lstm_ctc</a></p></li>
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<li><p><a class="reference external" href="https://github.com/k2-fsa/icefall/tree/master/egs/librispeech/ASR/conformer_ctc">egs/librispeech/conformer_ctc</a></p></li>
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</ul>
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</div></blockquote>
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<p>to get a feel what the resulting files look like.</p>
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</div>
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<div class="admonition note">
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<p class="admonition-title">Note</p>
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<p>Every model in a recipe is kept to be as self-contained as possible.
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We tolerate duplicate code among different recipes.</p>
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</div>
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<p>The training stage should be invocable by:</p>
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<blockquote>
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<div><div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ cd egs/foo/ASR
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$ ./bar/train.py
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$ ./bar/train.py --help
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</pre></div>
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</div>
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</div></blockquote>
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</section>
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<section id="decoding">
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<h2>Decoding<a class="headerlink" href="#decoding" title="Permalink to this heading"></a></h2>
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<p>Please refer to</p>
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<blockquote>
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<div><ul>
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<li><p><a class="reference external" href="https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/conformer_ctc/decode.py">https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/conformer_ctc/decode.py</a></p>
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<p>If your model is transformer/conformer based.</p>
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</li>
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<li><p><a class="reference external" href="https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/tdnn_lstm_ctc/decode.py">https://github.com/k2-fsa/icefall/blob/master/egs/librispeech/ASR/tdnn_lstm_ctc/decode.py</a></p>
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<p>If your model is TDNN/LSTM based, i.e., there is no attention decoder.</p>
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</li>
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<li><p><a class="reference external" href="https://github.com/k2-fsa/icefall/blob/master/egs/yesno/ASR/tdnn/decode.py">https://github.com/k2-fsa/icefall/blob/master/egs/yesno/ASR/tdnn/decode.py</a></p>
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<p>If there is no LM rescoring.</p>
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</li>
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</ul>
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</div></blockquote>
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<p>The decoding stage should be invocable by:</p>
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<blockquote>
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<div><div class="highlight-default notranslate"><div class="highlight"><pre><span></span>$ cd egs/foo/ASR
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$ ./bar/decode.py
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$ ./bar/decode.py --help
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</pre></div>
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</div>
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</div></blockquote>
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</section>
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<section id="pre-trained-model">
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<h2>Pre-trained model<a class="headerlink" href="#pre-trained-model" title="Permalink to this heading"></a></h2>
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<p>Please demonstrate how to use your model for inference in <code class="docutils literal notranslate"><span class="pre">egs/foo/ASR/bar/pretrained.py</span></code>.
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If possible, please consider creating a Colab notebook to show that.</p>
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</section>
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