The reference implementation for the papers

End-to-End Attention-based Large Vocabulary Speech Recognition. Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, Yoshua Bengio (arxiv draft, ICASSP 2016)

and

Task Loss Estimation for Sequence Prediction. Dzmitry Bahdanau, Dmitriy Serdyuk, Philémon Brakel, Nan Rosemary Ke, Jan Chorowski, Aaron Courville, Yoshua Bengio (arxiv draft, submitted to ICLR 2016).

• install all the dependencies (see the list below)
• set your environment variables by calling source env.sh

Then, please proceed to exp/wsj for the instructions how to replicate our results on Wall Street Journal (WSJ) dataset (available at the Linguistic Data Consortium as LDC93S6B and LDC94S13B).

• Python packages: pykwalify, toposort, pyyaml, numpy, pandas, pyfst, picklable-itertools;
• kaldi;
• kaldi-python.

Given that you have the dataset in HDF5 format, the models can be trained without Kaldi and PyFst.

• Compile Kaldi. It should be compiled with --shared option, it means that Kaldi should be configured like

  ./configure --shared
  

  we need Kaldi to be compiled in shared mode to be able to use kaldi-python.

  We don't train anything with Kaldi, so there is no need to compile it with cuda, so if you have any problems with Kaldi+CUDA, feel free to turn it off:

  ./configure --shared --use-cuda=no
  

  After this step you should have openfst installed at $KALDI_ROOT/tools/openfst.

• Install python packages. You can use pip for that:

  pip install pykwalify toposort pyyaml numpy pandas pyfst
  

• Install kaldi-python. Clone the repository and run

  python setup.py install
  

  kaldi-python will be compiled and installed to your system, you can check that everything went right by running

  python -c "import kaldi_io"
  

The repository contains custom modified versions of Theano, Blocks, Fuel, picklable-itertools, Blocks-extras as [subtrees] (http://blogs.atlassian.com/2013/05/alternatives-to-git-submodule-git-subtree/). In order to ensure that these specific versions are used, we recommend to uninstall regular installations of these packages if you have them installed in addition to sourcing env.sh.

MIT