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README.md
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README.md
@ -7,7 +7,6 @@
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* [Install icefall](#install-icefall)
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- [Run recipes](#run-recipes)
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## Installation
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`icefall` depends on [k2][k2] for FSA operations and [lhotse][lhotse] for
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@ -32,7 +31,7 @@ git clone https://github.com/k2-fsa/k2.git
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cd k2
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mkdir build_release
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cd build_release
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cmake -DCMAKE_BUILD_TYPE=Release
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cmake -DCMAKE_BUILD_TYPE=Release ..
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make -j _k2
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export PYTHONPATH=$HOME/open-source/k2/k2/python:$PYTHONPATH
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export PYTHONPATH=$HOME/open-source/k2/build_release/lib:$PYTHONPATH
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@ -40,7 +39,7 @@ export PYTHONPATH=$HOME/open-source/k2/build_release/lib:$PYTHONPATH
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To check that k2 is installed successfully, please run
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```
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```bash
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python3 -m k2.version
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```
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@ -57,7 +56,7 @@ lhotse.
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`icefall` is a set of Python scripts. What you need to do is just to set
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the environment variable `PYTHONPATH`:
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```
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```bash
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cd $HOME/open-source
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git clone https://github.com/k2-fsa/icefall
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cd icefall
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@ -67,17 +66,16 @@ export PYTHONPATH=$HOME/open-source/icefall:$PYTHONPATHON
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To verify `icefall` was installed successfully, you can run:
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```
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```bash
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python3 -c "import icefall; print(icefall.__file__)"
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```
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It should print the path to `icefall`.
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## Run recipes
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Currently only the LibriSpeech recipe is provided. Please
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follow the [egs/librispeech/ASR/README.md][LibriSpeech] to run it.
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At present, only LibriSpeech recipe is provided. Please
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follow [egs/librispeech/ASR/README.md][LibriSpeech] to run it.
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[LibriSpeech]: egs/librispeech/ASR/README.md
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[k2-install]: https://k2.readthedocs.io/en/latest/installation/index.html#
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@ -1,7 +1,7 @@
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## Data preparation
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If you want to `./prepare.sh` to download everything for you,
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If you want to use `./prepare.sh` to download everything for you,
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you can just run
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```
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@ -17,7 +17,7 @@ please run
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./prepare.sh
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```
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The script `./prepare.sh` prepare features, lexicon, LMs, etc.
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The script `./prepare.sh` prepares features, lexicon, LMs, etc.
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All generated files are saved in the folder `./data`.
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HINT: `./prepare.sh` support options `--stage` and `--stop-stage`.
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@ -31,7 +31,7 @@ Pre-configured parameters for training and decoding are set in the function
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`get_params()` within `tdnn_lstm_ctc/train.py`
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and `tdnn_lstm_ctc/decode.py`.
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Parameters that can be passed from commandlin can be found by
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Parameters that can be passed from the commandline can be found by
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```
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./tdnn_lstm_ctc/train.py --help
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