pygame GATE.ac.uk - index.html STAR Laboratory: SRI Language Modeling Toolkit SRILM is a toolkit for building and applying statistical language models (LMs), primarily for use in speech recognition, statistical tagging and segmentation, and machine translation. 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, 1997, and 2002 (see history). These pages and the software itself assume that you know what statistical language modeling is. Either book gives an excellent introduction to N-gram language modeling, which is the main type of LM supported by SRILM. SRILM consists of the following components: A set of C++ class libraries implementing language models, supporting data stuctures and miscellaneous utility functions. SRILM runs on UNIX and Windows platforms. SRILM has been used in a great variety of statistical modeling applications. Documentation SRILM is still under development.
Basic NLP in CoffeeScript or JavaScript -- Punkt tokenizaton, simple trained Bayes models -- where to start Astropython nltk.googlecode.com/svn/trunk/doc/book/ch00.html This is a book about Natural Language Processing. By "natural language" we mean a language that is used for everyday communication by humans; languages like English, Hindi or Portuguese. In contrast to artificial languages such as programming languages and mathematical notations, natural languages have evolved as they pass from generation to generation, and are hard to pin down with explicit rules. Technologies based on NLP are becoming increasingly widespread. This book provides a highly accessible introduction to the field of NLP. The book is based on the Python programming language together with an open source library called the Natural Language Toolkit (NLTK). Audience NLP is important for scientific, economic, social, and cultural reasons. This book is intended for a diverse range of people who want to learn how to write programs that analyze written language, regardless of previous programming experience: Emphasis This book is a practical introduction to NLP. What You Will Learn
pyquery pyquery allows you to make jquery queries on xml documents. The API is as much as possible the similar to jquery. pyquery uses lxml for fast xml and html manipulation. This is not (or at least not yet) a library to produce or interact with javascript code. I just liked the jquery API and I missed it in python so I told myself “Hey let’s make jquery in python”. This is the result. It can be used for many purposes, one idea that I might try in the future is to use it for templating with pure http templates that you modify using pyquery. The project is being actively developped on a git repository on Github. Please report bugs on the github issue tracker. You can use the PyQuery class to load an xml document from a string, a lxml document, from a file or from an url: Now d is like the $ in jquery: >>> d("#hello")[<p#hello.hello>]>>> p = d("#hello")>>> print(p.html())Hello world ! >>> d('p:first')[<p#hello.hello>] First there is the Sphinx documentation here.
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