SWIG-SRILM: A SWIG-based wrapper for an SRILM language model

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Description

This package contains files to generate Perl and Python wrappers for SRILM language models.

Requirements

• GNU make
• Simplified Wrapper & Interface Generator (SWIG)
• A local Python and/or Perl installation
• The SRILM toolkit (v1.7.1). If you have an older version of SRILM e.g., the 1.5.x series then you should use the old_srilm branch. Note that SRILM should have been compiled as position independent code. You can do that by using the command MAKE_PIC=yes make when compiling SRILM.

IMPORTANT: This code has been extensively tested on x86-64 machines running Linux. There's a branch (macosx) that should compile on the latest version of OS X 10.11 (assuming you have installed swig) but only with the built-in python (/usr/bin/python). Please freel free to try it and let me know if it does/doesn't work.

Installation:

• Modify the following environment variables at the top of the included Makefile:

• SRILM_LIBS : The directory containing the SRILM libraries

• SRILM_INC : The directory containing the SRILM header files

• PYTHON_INC : The directory containing the python header files

• PERL_INC : The directory containing the perl header files

• To create a Python module, run 'make python' in this directory. Copy _srilm.so and srilm.py to your directory where you want to use the python module. You can run the included test.py script to check whether the compiled module works correctly. The output of test.py should be the following:

1. Number of n-grams:
   There are 11868 unigrams in this LM
   There are 59481 bigrams in this LM
   There are 16744 trigrams in this LM
   There are 13787 4-grams in this LM
   There are 12082 5-grams in this LM

2. N-gram log probabilities:
   p('good') = -3.49373698235
   p('of the') = -0.558740794659
   p('nitin madnani') = -99.0
   p('there are some') = -0.985605716705
   p('do more about your') = -0.469523012638
   p('or whatever has yet to') = -0.53226429224

3. Sentence log probabilities and perplexities:
   p('there are some good') = -9.85836982727
   ppl('there are some good') = 93.6858444214

4. OOvs:
   nOOVs('there are some foobar') = 1

5. Corpus log probabilties and perplexities:
   Logprob for the file test.txt = -33.6016654968
   Perplexity for the file test.txt = 94.7476806641

• To create a Perl module, run make perl in this directory. Copy srilm.so and srilm.pm to the directory of your choice. Run the included Perl script 'test.pl' to test whether the compiled module works correctly. The output should be the same as above.

Usage:

Usage is clearly illustrated in files test.pl and test.py.