Tradubi: Open-Source Social Translation for the Apertium Machine Translation Platform

Abstract

Massive online collaboration could become a winning strategy to tear down the language barriers on the web, and in order for this to happen appropriate computer tools, like reliable machine translation systems and friendly postediting interfaces, should be widely available. However, community collaboration should not only involve the postediting of machine translations, but also the creation of the linguistic resources needed to improve the translation engines. In this paper we introduce Tradubi, a free/open-source web application for social translation, whose aim is, firstly, to build a platform for collaboratively customising and improving rule-based machine translation systems and, secondly, to offer an environment for the postediting and subsequent sharing of raw machine translations. Currently, Tradubi is built upon the free/open-source Apertium machine translation engine. The application can be accessed at tradubi.com or downloaded and installed on a different server.

A web-based translation service at the UOC based on Apertium

“…Linguistic data feeding the engine are coded in XML-based files which are compiled into binary format (finite-state letter-transducers [6]) to speed up the translation process (10,000 words can be processed per second on a basic desktop PC). An extensive documentation is also available 7 .…”

“…Since 2005, with the first release of the engine (which was aimed at dealing with closely related languages), tools and the Spanish↔Catalan and Spanish↔Galician pairs, the Apertium platform has been extended greatly: [7]. All these efforts result in the continuous improvement of the Apertium platform and are carried out by a worldwide community of developers and committers acting individually or as groups in companies, organizations, research groups, etc.…”

“…http://www.gnu.org/copyleft/gpl.html7 The Apertium Wiki provides documentation of a wide variety of development and usage scenarios (http://wiki.apertium.org/) 8. http://www.internostrum.com 9 http://traductor.universia.net…”

Getting Past the Language Gap: Innovations in Machine Translation

“…They have been added to SMT systems since its early days (Brown et al 1993). One of the simplest strategies, which has already been put into practice with the Apertium bilingual dictionaries (Tyers 2009;Sanchez-Cartagena and Pérez-Ortiz 2010), consists of adding the dictionary entries directly to the parallel corpus. In addition to the obvious increase in lexical coverage, Schwenk et al (2009) state that the quality of the alignments obtained is also improved when the words in the bilingual dictionary appear in other sentences of the parallel corpus.…”