Precision Translation Tools

http://precisiontranslationtools.com/ - the new source for Statistical Machine Translation (SMT) tools and resources.

NLP News

http://nlp.hivefire.com/

This site synthesizes news in Natural Language Processing (NLP) from various sources (webs, blogs) around the world. It's great!

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Vu

OpenCog - The Open Cognition Project

Link: http://wiki.opencog.org/w/The_Open_Cognition_Project

OpenCog - an open source Artificial General Intelligence framework, intended to one day express general intelligence at the human level and beyond.

A little bit ambitious?

RelEx Dependency Relationship Extractor

Link: https://launchpad.net/relex/

Documentation: http://wiki.opencog.org/w/RelEx

RelEx is an English-language dependency relationship extractor, built on the Carnegie-Mellon link parser. It can identify subject, object, indirect object and many other dependency relationships between words in a sentence. It also generates some advanced semantic relations, such as normalizing questions for question-answering. It also proposes "frames" or "semantic roles", similar in style to those of FrameNet. RelEx includes a basic implementation of the Hobbs anaphora (pronoun) resolution algorithm. As a "by-product", it also provides more basic functions, including entity detection, part-of-speech tagging, noun-number tagging, verb tense tagging, gender tagging, and so on. Relex now includes a Stanford parser compatibility mode, generating identical output, but more accurately and more quickly.

Alignment Set Toolkit

http://gps-tsc.upc.es/veu/personal/lambert/software/AlignmentSet.html

Training SMT incrementally

For word alignments

Force Alignment: http://geek.kyloo.net/software/doku.php/mgiza:forcealignment

MGIZA++: http://geek.kyloo.net/software/doku.php/mgiza:overview and http://sourceforge.net/projects/mgizapp/

For translation models

Stream-based Translation Models for Statistical Machine Translation

Abby Levenberg, Chris Callison-Burch and Miles Osborne, NAACL 2010.

For language models

Stream-based Randomised Language Models for SMT

Abby Levenberg and Miles Osborne, EMNLP 2009.

Discourse Parsing

Sentence-based level:
SPADE: http://www.isi.edu/licensed-sw/spade/

Text-base level:
HILDA: http://nlp.prendingerlab.net/hilda/
NUS demo: http://wing.comp.nus.edu.sg/~linzihen/parser/demo.html

(to be continued!)