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MITLM + Live Guessing

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MIT Language Modeling Toolkit
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The MIT Language Modeling (MITLM) toolkit is a set of tools designed for the 
efficient estimation of statistical n-gram language models involving iterative
parameter estimation.  It achieves much of its efficiency through the use of a
compact vector representation of n-grams.  Details of the data structure and
associated algorithms can be found in the following paper.

  * Bo-June (Paul) Hsu and James Glass.  Iterative Language Model Estimation:
    Efficient Data Structure & Algorithms.  In Proc. Interspeech, 2008. 

Currently, MITLM supports the following features:

  * Smoothing: Modified Kneser-Ney, Kneser-Ney, maximum likelihood
  * Interpolation: Linear interpolation, count merging, generalized linear
    interpolation
  * Evaluation: Perplexity
  * File formats: ARPA, binary, gzip, bz2 

MITLM is available for download under the MIT License. It has been built and 
tested on 32-bit and 64-bit Intel CPUs running Debian Linux 4.0. It currently
requires the following:

  * ANSI C++/Fortran compiler (GCC 4.1.2+)
  * Boost C++ Libraries (1.32+) 

===============
Acknowledgments
===============

The design and implementation of this toolkit benefited significantly from the
SRI Language Modeling Toolkit by Andreas Stolcke.  The vector library is
partially derived from the Flexible Library for Efficient Numerical Solutions
by Michael Lehn.

  Copyright (c) 2007, Michael Lehn

  All rights reserved.

  Redistribution and use in source and binary forms, with or without
  modification, are permitted provided that the following conditions are met:

  1) Redistributions of source code must retain the above copyright notice, 
     this list of conditions and the following disclaimer.
  2) Redistributions in binary form must reproduce the above copyright notice,
     this list of conditions and the following disclaimer in the documentation
     and/or other materials provided with the distribution.
  3) Neither the name of the FLENS development group nor the names of its
     contributors may be used to endorse or promote products derived from this
     software without specific prior written permission.

  THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
  "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT
  LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR
  A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT OWNER OR
  CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
  EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
  PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
  PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF
  LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING
  NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS
  SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

The project is supported in part by the T-Party Project, a joint research program between MIT CSAIL and Quanta Computer Inc.

Bo-June (Paul) Hsu
Computer Science and Artificial Intelligence Laboratory
Massachusetts Institute of Technology
(C) 2008 



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