MateCat leverages the growing interest and expectations in statistical MT along three directions: Self-tuning MT, User adaptive MT, Informative MT. The tool supports Unicode (UTF-8) encoding, including non-Latin alphabets and right-to-left languages, and handles texts embedding mark-up tags. XLIFF is the file format natively supported by the open source version of the MateCat tool however external file converters can be added in the MateCat configuration file. Communication with the Moses servers extends the GT API in order to support self-tuning, user-adaptive and informative MT functions. While MyMemory’s and GT’s servers are always running and available, customized Moses servers have to be first installed and set-up. The CAT web-server connects with other services via open APIs: the TM server MyMemory, the commercial Google Translate (GT) MT server, and a list of Moses -based servers specified in a configuration file. The MateCat tool runs as a web-server accessible through Chrome. The integration of suggestions from an MT engine as a complement to TM matches is motivated by recent studies, which have shown that post-editing MT suggestions substantially improves the level of accuracy in translations. Once a segment is translated, its source and target texts are added to the TM for future queries.
These matches are proposed to the user as translation suggestions. During translation, the CAT tool queries the TM to search for exact or fuzzy matches of the current source segment. A TM is a repository of translated segments. ĬAT tools provide access to translation memories (TMs), terminology databases, concordance tools and, more recently, to machine translation (MT) engines. The system is able to learn from mistakes, automatically improve over time and specialize in field-specific language (for example, legal terminology) to provide the user accurate translation suggestions in an automatic and transparent manner. The objective of MateCat is to create a tool to edit machine translation results and manage localization workflow. The project consortium is led by FBK ( Fondazione Bruno Kessler), an international research center based in Trento, Italy. It has received over €2,500,000 of European funds. MateCat, acronym of Machine Translation Enhanced Computer Assisted Translation, is a 3-year research project (11/2011-10/2014) funded by the European Union’s Seventh Framework Programme for research, technological development and demonstration under grant agreement #287688.
0 kommentar(er)
