Add stateless transducer tutorial. (#235)

* WIP: Add stateless transducer tutorial.

* Add more doc.

* Minor fixes.

docs/source/conf.py

@@ -33,6 +33,7 @@ release = "0.1"
 # ones.
 extensions = [
     "sphinx_rtd_theme",
+    "sphinx.ext.todo",
 ]
 
 # Add any paths that contain templates here, relative to this directory.
@@ -74,3 +75,5 @@ html_context = {
     "github_version": "master",
     "conf_py_path": "/icefall/docs/source/",
 }
+
+todo_include_todos = True

docs/source/installation/images/README.md

@@ -0,0 +1,4 @@
+
+# Introduction
+
+<https://shields.io/> is used to generate files in this directory.

docs/source/installation/images/k2-gt-v1.9-blueviolet.svg

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docs/source/installation/images/python-gt-v3.6-blue.svg

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docs/source/installation/images/torch-1.6.0_1.7.0_1.7.1_1.8.0_1.8.1_1.9.0-green.svg

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docs/source/installation/images/torch-gt-v1.6.0-green.svg

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docs/source/installation/index.rst

@@ -15,13 +15,13 @@ Installation
 .. |device| image:: ./images/device-CPU_CUDA-orange.svg
   :alt: Supported devices
 
-.. |python_versions| image:: ./images/python-3.6_3.7_3.8_3.9-blue.svg
+.. |python_versions| image:: ./images/python-gt-v3.6-blue.svg
   :alt: Supported python versions
 
-.. |torch_versions| image:: ./images/torch-1.6.0_1.7.0_1.7.1_1.8.0_1.8.1_1.9.0-green.svg
+.. |torch_versions| image:: ./images/torch-gt-v1.6.0-green.svg
   :alt: Supported PyTorch versions
 
-.. |k2_versions| image:: ./images/k2-v1.9-blueviolet.svg
+.. |k2_versions| image:: ./images/k2-gt-v1.9-blueviolet.svg
   :alt: Supported k2 versions
 
 ``icefall`` depends on `k2 <https://github.com/k2-fsa/k2>`_ and

docs/source/recipes/aishell.rst

@@ -1,10 +0,0 @@
-Aishell
-=======
-
-We provide the following models for the Aishell dataset:
-
-.. toctree::
-   :maxdepth: 2
-
-   aishell/conformer_ctc
-   aishell/tdnn_lstm_ctc

docs/source/recipes/aishell/index.rst

@@ -0,0 +1,22 @@
+aishell
+=======
+
+Aishell is an open-source Chinese Mandarin speech corpus published by Beijing
+Shell Shell Technology Co.,Ltd.
+
+400 people from different accent areas in China are invited to participate in
+the recording, which is conducted in a quiet indoor environment using high
+fidelity microphone and downsampled to 16kHz. The manual transcription accuracy
+is above 95%, through professional speech annotation and strict quality
+inspection. The data is free for academic use. We hope to provide moderate
+amount of data for new researchers in the field of speech recognition.
+
+It can be downloaded from `<https://www.openslr.org/33/>`_
+
+.. toctree::
+   :maxdepth: 1
+
+   tdnn_lstm_ctc
+   conformer_ctc
+   stateless_transducer
+

docs/source/recipes/aishell/stateless_transducer.rst

@@ -0,0 +1,714 @@
+Stateless Transducer
+====================
+
+This tutorial shows you how to do transducer training in ``icefall``.
+
+.. HINT::
+
+  Instead of using RNN-T or RNN transducer, we only use transducer
+  here. As you will see, there are no RNNs in the model.
+
+.. HINT::
+
+  We assume you have read the page :ref:`install icefall` and have setup
+  the environment for ``icefall``.
+
+.. HINT::
+
+  We recommend you to use a GPU or several GPUs to run this recipe.
+
+In this tutorial, you will learn:
+
+  - (1) What does the transducer model look like
+  - (2) How to prepare data for training and decoding
+  - (3) How to start the training, either with a single GPU or with multiple GPUs
+  - (4) How to do decoding after training, with greedy search, beam search and, **modified beam search**
+  - (5) How to use a pre-trained model provided by us to transcribe sound files
+
+
+The Model
+---------
+
+The transducer model consists of 3 parts:
+
+- **Encoder**: It is a conformer encoder with the following parameters
+
+    - Number of heads: 8
+    - Attention dim: 512
+    - Number of layers: 12
+    - Feedforward dim: 2048
+
+- **Decoder**: We use a stateless model consisting of:
+
+    - An embedding layer with embedding dim 512
+    - A Conv1d layer with a default kernel size 2 (i.e. it sees 2
+      symbols of left-context by default)
+
+- **Joiner**: It consists of a ``nn.tanh()`` and a ``nn.Linear()``.
+
+.. Caution::
+
+  The decoder is stateless and very simple. It is borrowed from
+  `<https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9054419>`_
+  (Rnn-Transducer with Stateless Prediction Network)
+
+  We make one modification to it: Place a Conv1d layer right after
+  the embedding layer.
+
+When using Chinese characters as modelling unit, whose vocabulary size
+is 4336 in this specific dataset,
+the number of parameters of the model is ``87939824``, i.e., about ``88 M``.
+
+The Loss
+--------
+
+We are using `<https://github.com/csukuangfj/optimized_transducer>`_
+to compute the transducer loss, which removes extra paddings
+in loss computation to save memory.
+
+.. Hint::
+
+  ``optimized_transducer`` implements the technqiues proposed
+  in `Improving RNN Transducer Modeling for End-to-End Speech Recognition <https://arxiv.org/abs/1909.12415>`_ to save memory.
+
+  Furthermore, it supports ``modified transducer``, limiting the maximum
+  number of symbols that can be emitted per frame to 1, which simplifies
+  the decoding process significantly. Also, the experiment results
+  show that it does not degrade the performance.
+
+  See `<https://github.com/csukuangfj/optimized_transducer#modified-transducer>`_
+  for what exactly modified transducer is.
+
+  `<https://github.com/csukuangfj/transducer-loss-benchmarking>`_ shows that
+  in the unpruned case ``optimized_transducer`` has the advantage about minimizing
+  memory usage.
+
+.. todo::
+
+  Add tutorial about ``pruned_transducer_stateless`` that uses k2
+  pruned transducer loss.
+
+.. hint::
+
+  You can use::
+
+    pip install optimized_transducer
+
+  to install ``optimized_transducer``. Refer to
+  `<https://github.com/csukuangfj/optimized_transducer>`_ for other
+  alternatives.
+
+Data Preparation
+----------------
+
+To prepare the data for training, please use the following commands:
+
+.. code-block:: bash
+
+  cd egs/aishell/ASR
+  ./prepare.sh --stop-stage 4
+  ./prepare.sh --stage 6 --stop-stage 6
+
+.. note::
+
+  You can use ``./prepare.sh``, though it will generate FSTs that
+  are not used in transducer training.
+
+When you finish running the script, you will get the following two folders:
+
+  - ``data/fbank``: It saves the pre-computed features
+  - ``data/lang_char``: It contains tokens that will be used in the training
+
+Training
+--------
+
+.. code-block:: bash
+
+  cd egs/aishell/ASR
+  ./transducer_stateless_modified/train.py --help
+
+shows you the training options that can be passed from the commandline.
+The following options are used quite often:
+
+  - ``--exp-dir``
+
+    The experiment folder to save logs and model checkpoints,
+    defaults to ``./transducer_stateless_modified/exp``.
+
+  - ``--num-epochs``
+
+    It is the number of epochs to train. For instance,
+    ``./transducer_stateless_modified/train.py --num-epochs 30`` trains for 30
+    epochs and generates ``epoch-0.pt``, ``epoch-1.pt``, ..., ``epoch-29.pt``
+    in the folder set by ``--exp-dir``.
+
+  - ``--start-epoch``
+
+    It's used to resume training.
+    ``./transducer_stateless_modified/train.py --start-epoch 10`` loads the
+    checkpoint from ``exp_dir/epoch-9.pt`` and starts
+    training from epoch 10, based on the state from epoch 9.
+
+  - ``--world-size``
+
+    It is used for single-machine multi-GPU DDP training.
+
+      - (a) If it is 1, then no DDP training is used.
+
+      - (b) If it is 2, then GPU 0 and GPU 1 are used for DDP training.
+
+    The following shows some use cases with it.
+
+      **Use case 1**: You have 4 GPUs, but you only want to use GPU 0 and
+      GPU 2 for training. You can do the following:
+
+        .. code-block:: bash
+
+          $ cd egs/aishell/ASR
+          $ export CUDA_VISIBLE_DEVICES="0,2"
+          $ ./transducer_stateless_modified/train.py --world-size 2
+
+      **Use case 2**: You have 4 GPUs and you want to use all of them
+      for training. You can do the following:
+
+        .. code-block:: bash
+
+          $ cd egs/aishell/ASR
+          $ ./transducer_stateless_modified/train.py --world-size 4
+
+      **Use case 3**: You have 4 GPUs but you only want to use GPU 3
+      for training. You can do the following:
+
+        .. code-block:: bash
+
+          $ cd egs/aishell/ASR
+          $ export CUDA_VISIBLE_DEVICES="3"
+          $ ./transducer_stateless_modified/train.py --world-size 1
+
+    .. CAUTION::
+
+      Only single-machine multi-GPU DDP training is implemented at present.
+      There is an on-going PR `<https://github.com/k2-fsa/icefall/pull/63>`_
+      that adds support for multi-machine multi-GPU DDP training.
+
+  - ``--max-duration``
+
+    It specifies the number of seconds over all utterances in a
+    batch **before padding**.
+    If you encounter CUDA OOM, please reduce it. For instance, if
+    your are using V100 NVIDIA GPU with 32 GB RAM, we recommend you
+    to set it to ``300`` when the vocabulary size is 500.
+
+    .. HINT::
+
+      Due to padding, the number of seconds of all utterances in a
+      batch will usually be larger than ``--max-duration``.
+
+      A larger value for ``--max-duration`` may cause OOM during training,
+      while a smaller value may increase the training time. You have to
+      tune it.
+
+  - ``--lr-factor``
+
+    It controls the learning rate. If you use a single GPU for training, you
+    may want to use a small value for it. If you use multiple GPUs for training,
+    you may increase it.
+
+  - ``--context-size``
+
+    It specifies the kernel size in the decoder. The default value 2 means it
+    functions as a tri-gram LM.
+
+  - ``--modified-transducer-prob``
+
+    It specifies the probability to use modified transducer loss.
+    If it is 0, then no modified transducer is used; if it is 1,
+    then it uses modified transducer loss for all batches. If it is
+    ``p``, it applies modified transducer with probability ``p``.
+
+There are some training options, e.g.,
+number of warmup steps,
+that are not passed from the commandline.
+They are pre-configured by the function ``get_params()`` in
+`transducer_stateless_modified/train.py <https://github.com/k2-fsa/icefall/blob/master/egs/aishell/ASR/transducer_stateless_modified/train.py#L162>`_
+
+If you need to change them, please modify ``./transducer_stateless_modified/train.py`` directly.
+
+.. CAUTION::
+
+  The training set is perturbed by speed with two factors: 0.9 and 1.1.
+  Each epoch actually processes ``3x150 == 450`` hours of data.
+
+Training logs
+~~~~~~~~~~~~~
+
+Training logs and checkpoints are saved in the folder set by ``--exp-dir``
+(defaults to ``transducer_stateless_modified/exp``). You will find the following files in that directory:
+
+  - ``epoch-0.pt``, ``epoch-1.pt``, ...
+
+    These are checkpoint files, containing model ``state_dict`` and optimizer ``state_dict``.
+    To resume training from some checkpoint, say ``epoch-10.pt``, you can use:
+
+      .. code-block:: bash
+
+        $ ./transducer_stateless_modified/train.py --start-epoch 11
+
+  - ``tensorboard/``
+
+    This folder contains TensorBoard logs. Training loss, validation loss, learning
+    rate, etc, are recorded in these logs. You can visualize them by:
+
+      .. code-block:: bash
+
+        $ cd transducer_stateless_modified/exp/tensorboard
+        $ tensorboard dev upload --logdir . --name "Aishell transducer training with icefall" --description "Training modified transducer, see https://github.com/k2-fsa/icefall/pull/219"
+
+    It will print something like below:
+
+      .. code-block::
+
+        TensorFlow installation not found - running with reduced feature set.
+        Upload started and will continue reading any new data as it's added to the logdir.
+
+        To stop uploading, press Ctrl-C.
+
+        New experiment created. View your TensorBoard at: https://tensorboard.dev/experiment/laGZ6HrcQxOigbFD5E0Y3Q/
+
+        [2022-03-03T14:29:45] Started scanning logdir.
+        [2022-03-03T14:29:48] Total uploaded: 8477 scalars, 0 tensors, 0 binary objects
+        Listening for new data in logdir...
+
+    Note there is a `URL <https://tensorboard.dev/experiment/laGZ6HrcQxOigbFD5E0Y3Q/>`_ in the
+    above output, click it and you will see the following screenshot:
+
+      .. figure:: images/aishell-transducer_stateless_modified-tensorboard-log.png
+         :width: 600
+         :alt: TensorBoard screenshot
+         :align: center
+         :target: https://tensorboard.dev/experiment/laGZ6HrcQxOigbFD5E0Y3Q
+
+         TensorBoard screenshot.
+
+  - ``log/log-train-xxxx``
+
+    It is the detailed training log in text format, same as the one
+    you saw printed to the console during training.
+
+Usage examples
+~~~~~~~~~~~~~~
+
+The following shows typical use cases:
+
+**Case 1**
+^^^^^^^^^^
+
+.. code-block:: bash
+
+  $ cd egs/aishell/ASR
+  $ ./transducer_stateless_modified/train.py --max-duration 250
+
+It uses ``--max-duration`` of 250 to avoid OOM.
+
+
+**Case 2**
+^^^^^^^^^^
+
+.. code-block:: bash
+
+  $ cd egs/aishell/ASR
+  $ export CUDA_VISIBLE_DEVICES="0,3"
+  $ ./transducer_stateless_modified/train.py --world-size 2
+
+It uses GPU 0 and GPU 3 for DDP training.
+
+**Case 3**
+^^^^^^^^^^
+
+.. code-block:: bash
+
+  $ cd egs/aishell/ASR
+  $ ./transducer_stateless_modified/train.py --num-epochs 10 --start-epoch 3
+
+It loads checkpoint ``./transducer_stateless_modified/exp/epoch-2.pt`` and starts
+training from epoch 3. Also, it trains for 10 epochs.
+
+Decoding
+--------
+
+The decoding part uses checkpoints saved by the training part, so you have
+to run the training part first.
+
+.. code-block:: bash
+
+  $ cd egs/aishell/ASR
+  $ ./transducer_stateless_modified/decode.py --help
+
+shows the options for decoding.
+
+The commonly used options are:
+
+  - ``--method``
+
+    This specifies the decoding method. Currently, it supports:
+
+      - **greedy_search**. You can provide the commandline option ``--max-sym-per-frame``
+        to limit the maximum number of symbols that can be emitted per frame.
+
+      - **beam_search**. You can provide the commandline option ``--beam-size``.
+
+      - **modified_beam_search**. You can also provide the commandline option ``--beam-size``.
+        To use this method, we assume that you have trained your model with modified transducer,
+        i.e., used the option ``--modified-transducer-prob`` in the training.
+
+    The following command uses greedy search for decoding
+
+    .. code-block::
+
+      $ cd egs/aishell/ASR
+      $ ./transducer_stateless_modified/decode.py \
+              --epoch 64 \
+              --avg 33 \
+              --exp-dir ./transducer_stateless_modified/exp \
+              --max-duration 100 \
+              --decoding-method greedy_search \
+              --max-sym-per-frame 1
+
+    The following command uses beam search for decoding
+
+    .. code-block::
+
+      $ cd egs/aishell/ASR
+      $ ./transducer_stateless_modified/decode.py \
+              --epoch 64 \
+              --avg 33 \
+              --exp-dir ./transducer_stateless_modified/exp \
+              --max-duration 100 \
+              --decoding-method beam_search \
+              --beam-size 4
+
+    The following command uses ``modified`` beam search for decoding
+
+    .. code-block::
+
+      $ cd egs/aishell/ASR
+      $ ./transducer_stateless_modified/decode.py \
+              --epoch 64 \
+              --avg 33 \
+              --exp-dir ./transducer_stateless_modified/exp \
+              --max-duration 100 \
+              --decoding-method modified_beam_search \
+              --beam-size 4
+
+  - ``--max-duration``
+
+    It has the same meaning as the one used in training. A larger
+    value may cause OOM.
+
+  - ``--epoch``
+
+    It specifies the checkpoint from which epoch that should be used for decoding.
+
+  - ``--avg``
+
+    It specifies the number of models to average. For instance, if it is 3 and if
+    ``--epoch=10``, then it averages the checkpoints ``epoch-8.pt``, ``epoch-9.pt``,
+    and ``epoch-10.pt`` and the averaged checkpoint is used for decoding.
+
+After decoding, you can find the decoding logs and results in `exp_dir/log/<decoding_method>`, e.g.,
+``exp_dir/log/greedy_search``.
+
+Pre-trained Model
+-----------------
+
+We have uploaded a pre-trained model to
+`<https://huggingface.co/csukuangfj/icefall-aishell-transducer-stateless-modified-2022-03-01>`_
+
+We describe how to use the pre-trained model to transcribe a sound file or
+multiple sound files in the following.
+
+Install kaldifeat
+~~~~~~~~~~~~~~~~~
+
+`kaldifeat <https://github.com/csukuangfj/kaldifeat>`_ is used to
+extract features for a single sound file or multiple sound files
+at the same time.
+
+Please refer to `<https://github.com/csukuangfj/kaldifeat>`_ for installation.
+
+Download the pre-trained model
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The following commands describe how to download the pre-trained model:
+
+.. code-block::
+
+  $ cd egs/aishell/ASR
+  $ mkdir tmp
+  $ cd tmp
+  $ git lfs install
+  $ git clone https://huggingface.co/csukuangfj/icefall-aishell-transducer-stateless-modified-2022-03-01
+
+
+.. CAUTION::
+
+  You have to use ``git lfs`` to download the pre-trained model.
+
+After downloading, you will have the following files:
+
+.. code-block:: bash
+
+  $ cd egs/aishell/ASR
+  $ tree tmp/icefall-aishell-transducer-stateless-modified-2022-03-01
+
+
+.. code-block:: bash
+
+  tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/
+  |-- README.md
+  |-- data
+  |   `-- lang_char
+  |       |-- L.pt
+  |       |-- lexicon.txt
+  |       |-- tokens.txt
+  |       `-- words.txt
+  |-- exp
+  |   `-- pretrained.pt
+  |-- log
+  |   |-- errs-test-beam_4-epoch-64-avg-33-beam-4.txt
+  |   |-- errs-test-greedy_search-epoch-64-avg-33-context-2-max-sym-per-frame-1.txt
+  |   |-- log-decode-epoch-64-avg-33-beam-4-2022-03-02-12-05-03
+  |   |-- log-decode-epoch-64-avg-33-context-2-max-sym-per-frame-1-2022-02-28-18-13-07
+  |   |-- recogs-test-beam_4-epoch-64-avg-33-beam-4.txt
+  |   `-- recogs-test-greedy_search-epoch-64-avg-33-context-2-max-sym-per-frame-1.txt
+  `-- test_wavs
+      |-- BAC009S0764W0121.wav
+      |-- BAC009S0764W0122.wav
+      |-- BAC009S0764W0123.wav
+      `-- transcript.txt
+
+  5 directories, 16 files
+
+
+**File descriptions**:
+
+  - ``data/lang_char``
+
+    It contains language related files. You can find the vocabulary size in ``tokens.txt``.
+
+  - ``exp/pretrained.pt``
+
+      It contains pre-trained model parameters, obtained by averaging
+      checkpoints from ``epoch-32.pt`` to ``epoch-64.pt``.
+      Note: We have removed optimizer ``state_dict`` to reduce file size.
+
+  - ``log``
+
+      It contains decoding logs and decoded results.
+
+  - ``test_wavs``
+
+      It contains some test sound files from Aishell ``test`` dataset.
+
+The information of the test sound files is listed below:
+
+.. code-block:: bash
+
+  $ soxi tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/*.wav
+
+  Input File     : 'tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav'
+  Channels       : 1
+  Sample Rate    : 16000
+  Precision      : 16-bit
+  Duration       : 00:00:04.20 = 67263 samples ~ 315.295 CDDA sectors
+  File Size      : 135k
+  Bit Rate       : 256k
+  Sample Encoding: 16-bit Signed Integer PCM
+
+
+  Input File     : 'tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav'
+  Channels       : 1
+  Sample Rate    : 16000
+  Precision      : 16-bit
+  Duration       : 00:00:04.12 = 65840 samples ~ 308.625 CDDA sectors
+  File Size      : 132k
+  Bit Rate       : 256k
+  Sample Encoding: 16-bit Signed Integer PCM
+
+
+  Input File     : 'tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav'
+  Channels       : 1
+  Sample Rate    : 16000
+  Precision      : 16-bit
+  Duration       : 00:00:04.00 = 64000 samples ~ 300 CDDA sectors
+  File Size      : 128k
+  Bit Rate       : 256k
+  Sample Encoding: 16-bit Signed Integer PCM
+
+  Total Duration of 3 files: 00:00:12.32
+
+Usage
+~~~~~
+
+.. code-block::
+
+  $ cd egs/aishell/ASR
+  $ ./transducer_stateless_modified/pretrained.py --help
+
+displays the help information.
+
+It supports three decoding methods:
+
+  - greedy search
+  - beam search
+  - modified beam search
+
+.. note::
+
+  In modified beam search, it limits the maximum number of symbols that can be
+  emitted per frame to 1. To use this method, you have to ensure that your model
+  has been trained with the option ``--modified-transducer-prob``. Otherwise,
+  it may give you poor results.
+
+Greedy search
+^^^^^^^^^^^^^
+
+The command to run greedy search is given below:
+
+.. code-block:: bash
+
+
+  $ cd egs/aishell/ASR
+  $ ./transducer_stateless_modified/pretrained.py \
+      --checkpoint ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/exp/pretrained.pt \
+      --lang-dir ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char \
+      --method greedy_search \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav
+
+The output is as follows:
+
+.. code-block::
+
+  2022-03-03 15:35:26,531 INFO [pretrained.py:239] device: cuda:0
+  2022-03-03 15:35:26,994 INFO [lexicon.py:176] Loading pre-compiled tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char/Linv.pt
+  2022-03-03 15:35:27,027 INFO [pretrained.py:246] {'feature_dim': 80, 'encoder_out_dim': 512, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f4fefe4882bc0ae59af951da3f47335d5495ef71', 'k2-git-date': 'Thu Feb 10 15:16:02 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': '50d2281-clean', 'icefall-git-date': 'Wed Mar 2 16:02:38 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-aishell', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-multi-datasets/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-aishell/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-2-0815224919-75d558775b-mmnv8', 'IP address': '10.177.72.138'}, 'sample_rate': 16000, 'checkpoint': './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/exp/pretrained.pt', 'lang_dir': PosixPath('tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char'), 'method': 'greedy_search', 'sound_files': ['./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav'], 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 3, 'blank_id': 0, 'vocab_size': 4336}
+  2022-03-03 15:35:27,027 INFO [pretrained.py:248] About to create model
+  2022-03-03 15:35:36,878 INFO [pretrained.py:257] Constructing Fbank computer
+  2022-03-03 15:35:36,880 INFO [pretrained.py:267] Reading sound files: ['./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav']
+  2022-03-03 15:35:36,891 INFO [pretrained.py:273] Decoding started
+  /ceph-fj/fangjun/open-source-2/icefall-aishell/egs/aishell/ASR/transducer_stateless_modified/conformer.py:113: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
+    lengths = ((x_lens - 1) // 2 - 1) // 2
+  2022-03-03 15:35:37,163 INFO [pretrained.py:320]
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav:
+  甚 至 出 现 交 易 几 乎 停 滞 的 情 况
+
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav:
+  一 二 线 城 市 虽 然 也 处 于 调 整 中
+
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav:
+  但 因 为 聚 集 了 过 多 公 共 资 源
+
+  2022-03-03 15:35:37,163 INFO [pretrained.py:322] Decoding Done
+
+Beam search
+^^^^^^^^^^^
+
+The command to run beam search is given below:
+
+.. code-block:: bash
+
+
+  $ cd egs/aishell/ASR
+
+  $ ./transducer_stateless_modified/pretrained.py \
+      --checkpoint ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/exp/pretrained.pt \
+      --lang-dir ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char \
+      --method beam_search \
+      --beam-size 4 \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav
+
+The output is as follows:
+
+.. code-block::
+
+  2022-03-03 15:39:09,285 INFO [pretrained.py:239] device: cuda:0
+  2022-03-03 15:39:09,708 INFO [lexicon.py:176] Loading pre-compiled tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char/Linv.pt
+  2022-03-03 15:39:09,759 INFO [pretrained.py:246] {'feature_dim': 80, 'encoder_out_dim': 512, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f4fefe4882bc0ae59af951da3f47335d5495ef71', 'k2-git-date': 'Thu Feb 10 15:16:02 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': '50d2281-clean', 'icefall-git-date': 'Wed Mar 2 16:02:38 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-aishell', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-multi-datasets/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-aishell/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-2-0815224919-75d558775b-mmnv8', 'IP address': '10.177.72.138'}, 'sample_rate': 16000, 'checkpoint': './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/exp/pretrained.pt', 'lang_dir': PosixPath('tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char'), 'method': 'beam_search', 'sound_files': ['./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav'], 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 3, 'blank_id': 0, 'vocab_size': 4336}
+  2022-03-03 15:39:09,760 INFO [pretrained.py:248] About to create model
+  2022-03-03 15:39:18,919 INFO [pretrained.py:257] Constructing Fbank computer
+  2022-03-03 15:39:18,922 INFO [pretrained.py:267] Reading sound files: ['./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav']
+  2022-03-03 15:39:18,929 INFO [pretrained.py:273] Decoding started
+  /ceph-fj/fangjun/open-source-2/icefall-aishell/egs/aishell/ASR/transducer_stateless_modified/conformer.py:113: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
+    lengths = ((x_lens - 1) // 2 - 1) // 2
+  2022-03-03 15:39:21,046 INFO [pretrained.py:320]
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav:
+  甚 至 出 现 交 易 几 乎 停 滞 的 情 况
+
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav:
+  一 二 线 城 市 虽 然 也 处 于 调 整 中
+
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav:
+  但 因 为 聚 集 了 过 多 公 共 资 源
+
+  2022-03-03 15:39:21,047 INFO [pretrained.py:322] Decoding Done
+
+Modified Beam search
+^^^^^^^^^^^^^^^^^^^^
+
+The command to run modified beam search is given below:
+
+.. code-block:: bash
+
+
+  $ cd egs/aishell/ASR
+
+  $ ./transducer_stateless_modified/pretrained.py \
+      --checkpoint ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/exp/pretrained.pt \
+      --lang-dir ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char \
+      --method modified_beam_search \
+      --beam-size 4 \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav \
+      ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav
+
+The output is as follows:
+
+.. code-block::
+
+  2022-03-03 15:41:23,319 INFO [pretrained.py:239] device: cuda:0
+  2022-03-03 15:41:23,798 INFO [lexicon.py:176] Loading pre-compiled tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char/Linv.pt
+  2022-03-03 15:41:23,831 INFO [pretrained.py:246] {'feature_dim': 80, 'encoder_out_dim': 512, 'subsampling_factor': 4, 'attention_dim': 512, 'nhead': 8, 'dim_feedforward': 2048, 'num_encoder_layers': 12, 'vgg_frontend': False, 'env_info': {'k2-version': '1.13', 'k2-build-type': 'Release', 'k2-with-cuda': True, 'k2-git-sha1': 'f4fefe4882bc0ae59af951da3f47335d5495ef71', 'k2-git-date': 'Thu Feb 10 15:16:02 2022', 'lhotse-version': '1.0.0.dev+missing.version.file', 'torch-cuda-available': True, 'torch-cuda-version': '10.2', 'python-version': '3.8', 'icefall-git-branch': 'master', 'icefall-git-sha1': '50d2281-clean', 'icefall-git-date': 'Wed Mar 2 16:02:38 2022', 'icefall-path': '/ceph-fj/fangjun/open-source-2/icefall-aishell', 'k2-path': '/ceph-fj/fangjun/open-source-2/k2-multi-datasets/k2/python/k2/__init__.py', 'lhotse-path': '/ceph-fj/fangjun/open-source-2/lhotse-aishell/lhotse/__init__.py', 'hostname': 'de-74279-k2-train-2-0815224919-75d558775b-mmnv8', 'IP address': '10.177.72.138'}, 'sample_rate': 16000, 'checkpoint': './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/exp/pretrained.pt', 'lang_dir': PosixPath('tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/data/lang_char'), 'method': 'modified_beam_search', 'sound_files': ['./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav'], 'beam_size': 4, 'context_size': 2, 'max_sym_per_frame': 3, 'blank_id': 0, 'vocab_size': 4336}
+  2022-03-03 15:41:23,831 INFO [pretrained.py:248] About to create model
+  2022-03-03 15:41:32,214 INFO [pretrained.py:257] Constructing Fbank computer
+  2022-03-03 15:41:32,215 INFO [pretrained.py:267] Reading sound files: ['./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav', './tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav']
+  2022-03-03 15:41:32,220 INFO [pretrained.py:273] Decoding started
+  /ceph-fj/fangjun/open-source-2/icefall-aishell/egs/aishell/ASR/transducer_stateless_modified/conformer.py:113: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
+    lengths = ((x_lens - 1) // 2 - 1) // 2
+  /ceph-fj/fangjun/open-source-2/icefall-aishell/egs/aishell/ASR/transducer_stateless_modified/beam_search.py:402: UserWarning: __floordiv__ is deprecated, and its behavior will change in a future version of pytorch. It currently rounds toward 0 (like the 'trunc' function NOT 'floor'). This results in incorrect rounding for negative values. To keep the current behavior, use torch.div(a, b, rounding_mode='trunc'), or for actual floor division, use torch.div(a, b, rounding_mode='floor').
+    topk_hyp_indexes = topk_indexes // logits.size(-1)
+  2022-03-03 15:41:32,583 INFO [pretrained.py:320]
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0121.wav:
+  甚 至 出 现 交 易 几 乎 停 滞 的 情 况
+
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0122.wav:
+  一 二 线 城 市 虽 然 也 处 于 调 整 中
+
+  ./tmp/icefall-aishell-transducer-stateless-modified-2022-03-01/test_wavs/BAC009S0764W0123.wav:
+  但 因 为 聚 集 了 过 多 公 共 资 源
+
+  2022-03-03 15:41:32,583 INFO [pretrained.py:322] Decoding Done
+
+Colab notebook
+--------------
+
+We provide a colab notebook for this recipe showing how to use a pre-trained model to
+transcribe sound files.
+
+|aishell asr stateless modified transducer colab notebook|
+
+.. |aishell asr stateless modified transducer colab notebook| image:: https://colab.research.google.com/assets/colab-badge.svg
+   :target: https://colab.research.google.com/drive/12jpTxJB44vzwtcmJl2DTdznW0OawPb9H?usp=sharing

docs/source/recipes/index.rst

@@ -10,12 +10,10 @@ We may add recipes for other tasks as well in the future.
 .. Other recipes are listed in a alphabetical order.
 
 .. toctree::
-   :maxdepth: 3
+   :maxdepth: 2
+   :caption: Table of Contents
 
-   yesno
+   aishell/index
-
+   librispeech/index
-   librispeech
+   timit/index
-
+   yesno/index
-   aishell
-
-   timit

docs/source/recipes/librispeech.rst

@@ -1,10 +0,0 @@
-LibriSpeech
-===========
-
-We provide the following models for the LibriSpeech dataset:
-
-.. toctree::
-   :maxdepth: 2
-
-   librispeech/tdnn_lstm_ctc
-   librispeech/conformer_ctc

docs/source/recipes/librispeech/index.rst

@@ -0,0 +1,8 @@
+LibriSpeech
+===========
+
+.. toctree::
+   :maxdepth: 1
+
+   tdnn_lstm_ctc
+   conformer_ctc

docs/source/recipes/timit.rst

@@ -1,10 +0,0 @@
-TIMIT
-===========
-
-We provide the following models for the TIMIT dataset:
-
-.. toctree::
-   :maxdepth: 2
-
-   timit/tdnn_lstm_ctc
-   timit/tdnn_ligru_ctc

docs/source/recipes/timit/index.rst

@@ -0,0 +1,9 @@
+TIMIT
+=====
+
+.. toctree::
+   :maxdepth: 1
+
+   tdnn_ligru_ctc
+   tdnn_lstm_ctc
+

docs/source/recipes/timit/tdnn_ligru_ctc.rst

@@ -1,5 +1,5 @@
 TDNN-LiGRU-CTC
-=============
+==============
 
 This tutorial shows you how to run a TDNN-LiGRU-CTC model with the `TIMIT <https://data.deepai.org/timit.zip>`_ dataset.
 

docs/source/recipes/yesno/index.rst

@@ -0,0 +1,7 @@
+YesNo
+=====
+
+.. toctree::
+   :maxdepth: 1
+
+   tdnn

docs/source/recipes/yesno/tdnn.rst

@@ -1,5 +1,5 @@
-yesno
+TDNN-CTC
-=====
+========
 
 This page shows you how to run the `yesno <https://www.openslr.org/1>`_ recipe. It contains:
 
@@ -145,7 +145,7 @@ In ``tdnn/exp``, you will find the following files:
     Note there is a URL in the above output, click it and you will see
     the following screenshot:
 
-      .. figure:: images/yesno-tdnn-tensorboard-log.png
+      .. figure:: images/tdnn-tensorboard-log.png
          :width: 600
          :alt: TensorBoard screenshot
          :align: center

egs/aishell/ASR/README.md

@@ -1,7 +1,7 @@
 
 # Introduction
 
-Please refer to <https://icefall.readthedocs.io/en/latest/recipes/aishell.html>
+Please refer to <https://icefall.readthedocs.io/en/latest/recipes/aishell/index.html>
 for how to run models in this recipe.
 
 # Transducers

egs/librispeech/ASR/README.md

@@ -1,7 +1,7 @@
 
 # Introduction
 
-Please refer to <https://icefall.readthedocs.io/en/latest/recipes/librispeech.html>
+Please refer to <https://icefall.readthedocs.io/en/latest/recipes/librispeech/index.html>
 for how to run models in this recipe.
 
 # Transducers

egs/timit/ASR/README.md

@@ -1,3 +1,3 @@
 
-Please refer to <https://icefall.readthedocs.io/en/latest/recipes/timit.html>
+Please refer to <https://icefall.readthedocs.io/en/latest/recipes/timit/index.html>
 for how to run models in this recipe.

egs/yesno/ASR/README.md

@@ -10,5 +10,5 @@ get the following WER:
 ```
 
 Please refer to
-<https://icefall.readthedocs.io/en/latest/recipes/yesno.html>
+<https://icefall.readthedocs.io/en/latest/recipes/yesno/index.html>
 for detailed instructions.