Skip to content
finite-state toolkit, EM and Bayesian (Gibbs sampling) training for FST and context-free derivation forests
C++ Forth Shell Python Perl Emacs Lisp Other
Branch: master
Clone or download
Pull request Compare This branch is even with mobydobius:master.
Fetching latest commit…
Cannot retrieve the latest commit at this time.
Permalink
Type Name Latest commit message Commit time
Failed to load latest commit information.
balance
carmel
cipher
clm
cmake
forest-em
gextract
graehl
sblm
utf8
util
.clang-format
.gitattributes
.gitignore
CMakeLists.txt
LICENSE
Makefile
README.md
catn0.cc
utf8.h

README.md

Carmel finite-state toolkit - J. Graehl

(carmel includes EM and gibbs-sampled (pseudo-Bayesian) training)

(see carmel/LICENSE - free for research/non-commercial)

(see carmel/README and carmel/carmel-tutorial).

Building from source

mkdir build
cd build
cmake ..
make
make install

optional cmake parameters:

  • -DCMAKE_INSTALL_PREFIX=/custom/install/path
  • -DBOOST_ROOT=/path/to/boost (if it is not installed in standard location)
  • -DOPENFST_ROOT=/path/to/openfst (if desired, and it is not installed in standard location)

prerequisites:

  • cmake 3.1 or higher
  • a C++11 compiler
  • Boost. Tested on versions between 1.53 and 1.59, but others should work, too
  • Optionally, openfst (http://www.openfst.org)

Subdirectories

  • carmel: finite state transducer toolkit with EM and gibbs-sampled (pseudo-Bayesian) training

  • forest-em: derivation forests EM and gibbs (dirichlet prior bayesian) training

  • graehl/shared: utility C++/Make libraries used by carmel and forest-em

  • gextract: some python bayesian syntax MT rule inference

  • sblm: some simple pcfg (e.g. penn treebank parses, but preferably binarized)

  • clm: some class-based LM feature? I forget.

  • cipher: some word-class discovery and unsupervised decoding of simple probabilistic substitution cipher (uses carmel, but look to the tutorial in carmel/ first)

  • util: misc shell/perl scripts

You can’t perform that action at this time.