SRILM is a toolkit for building and applying statistical language models (LMs),
primarily for use in speech recognition, statistical tagging and segmentation.
It has been under development in the SRI Speech Technology and
Research Laboratory since 1995. The toolkit has also greatly benefitted from
its use and enhancements during the Johns Hopkins University/CLSP summer
workshops in 1995, 1996, and 1997
SRILM consists of the following components:
* A set of C++ class libraries implementing language models,
supporting data stuctures and miscellaneous utility functions.
* A set of executable programs built on top of these libraries to
perform standard tasks such as training LMs and testing them on
data, tagging or segmenting text, etc.
* A collection of miscellaneous scripts facilitating minor related tasks.
Submitted by: Cheng-Lung Sung <email@example.com>