The reference implementation for the paper

End-to-End Attention-based Large Vocabulary Speech Recognition. Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, Yoshua Bengio.

(arxiv draft, submitted to ICASSP 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 instructins 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
• kaldi
• kaldi-python

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

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