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Fork of Kaldi for developing custom recognisers for Alex spoken dialogue system framework

News & info

  • We use Docker <>_ so you can try easily our decoding demo

    • Run the demo using the two commands:

      1. download image docker pull ufaldsg/pykaldi
      2. run the demo docker run ufaldsg/pykaldi /bin/bash -c "cd online_demo; make gmm-latgen-faster; make online-recogniser; make pyonline-recogniser"

        • Note the demo downloads the pretrained models and test data which you may safe using docker commit functionality
    • Start exploring the demo source codes online_demo/ <>_ and onl-rec/ <>_

    • Please note, that you need to change the source code of Pykaldi in the docker image to effect the demo behaviour when using docker.
  • The Python wrapper of C++ OnlineLatticeRecogniser implements MFCC, LDA+MLLT, bMMI acoustic models since it was the best speaker independent setup.

  • UPDATE: Since 11/18/2014 the Pykaldi fork uses the Kaldi official code (src/online2) which has very similar as our previous implementation (and was finished roughly 8 month after our implementations).


.. image::

  • Our priority is to deploy it on Ubuntu 14.04 and also keep Travis running on Ubuntu 12.04
  • Read INSTALL.rst <./INSTALL.rst>_ and INSTALL <./INSTALL>_ first!
  • INSTALL.rst <./INSTALL.rst>_ contains instructions specific for this fork.
    INSTALL <./INSTALL>_ stores general instructions for Kaldi.



The fork presented three new Kaldi features in thesis of Ondrej Platek (see commit 8e534b16bb8a350):

  • Training scripts which can be used with standard Kaldi tools or with the new OnlineLatticeRecogniser.
    The scripts for Czech and English support acoustic models obtained using MFCC, LDA+MLLT/delta+delta-delta feature transformations and acoustic models trained generatively or by MPE or bMMI training.

The new functionality was separated to different directories:

  • pykaldi/src/onl-rec stores C++ code for OnlineLatticeRecogniser.
  • pykaldi/pykaldi stores Python wrapper PyOnlineLatticeRecogniser.
  • kaldi/egs/vystadial_{cz,en}/s5 stores training scripts. [merged to oficial Kaldi repo]
  • kaldi/online_demo shows Kaldi standard decoder, OnlineLatticeRecogniser and PyOnlineLatticeRecogniser, which produce the exact same lattices using the same setup.

The OnlineLatticeRecogniser is used in Alex dialogue system (

In March 2014, the PyOnlineLatticeRecogniser recogniser was evaluated on Alex domain.
See graphs evaluating OnlineLatticeRecogniser performance at

An example posterior word lattice output for one Czech utterance can be seen at

Other info

  • This Kaldi fork is developed under Vystadial project <>_.
  • Based on the Svn trunk of Kaldi project <svn://>_ which is mirrored to branch svn-mirror.
  • The svn trunk is mirrored via git svn.
    Checkout tutorials: Git svn <>,
    Svn branch in git <>
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