| Projects on Google Code | Results 1 - 10 of 12 |
=Summary=
A transduction parser is the basis for NLP tasks such as paraphrasing and machine translation. This parser supports transduction via weighted synchronous context free grammar rules.
treegraft is currently in the beta stage of development by Jonathan Clark (http://www.cs.cmu.edu/~jhcl...
The BerkeleyAligner is a word alignment software package that implements recent innovations in unsupervised word alignment. To learn more about the project and surrounding research, visit [http://nlp.cs.berkeley.edu/pages/WordAligner.html the Berkeley word aligner website].
===News===
*9/28* ...
Anusaaraka is an approach to Machine Translation based on Information Dynamics, inspired by Panini's grammar. It enables a person who knows any one Indian language, to understand texts in other languages like Sanskrit, Telugu, Kannada, or English. However the user needs some training to use the soft...
Resources for Quechua-to-English MT
This is api for partial machine translation to help human translators translating specific messages, like messages that contains plurals.
*Extract-Tmx-Corpus* is a Windows program (Vista and XP supported) that enables translators not necessarily with a deep knowledge of linguistic tools to create highly customised corpora that can be used with the Moses machine translation system and with other systems.
In order to create corpora...
NLP,
corpora,
MT,
Moses,
TMX,
SMT,
Python,
NaturalLanguageProcessing,
MachineTranslation,
StatisticalMachineTranslation
This site offers a set of 3 scripts that, together, create a basic translation chain prototype (with Moses + IRSTLM) able of processing very large corpora. The idea is to help build a translation chain for the real world, but it should also enable a quick evaluation of Moses for actual translation w...
This project is currently being developed privately. It is in very early stages of development. If you have any questions contact the project owner.
Based on back-translation technique, forming a good human-centric feedback system.
Now, we are planning to use the Google AJAX Language API.
A trial project to see how this works