OpenMaTrEx: A Free/Open-Source Marker-Driven Example-Based Machine Translation System
نویسندگان
چکیده
We describe OpenMaTrEx, a free/open-source examplebased machine translation (EBMT) system based on the marker hypothesis, comprising a marker-driven chunker, a collection of chunk aligners, and two engines: one based on a simple proof-of-concept monotone EBMT recombinator and a Moses-based statistical decoder. OpenMaTrEx is a free/open-source release of the basic components of MaTrEx, the Dublin City University machine translation system.
منابع مشابه
Technical report : OpenMaTrEx , a free , open - source hybrid data - driven machine translation system ∗
This report describes OpenMaTrEx, a free/open-source hybrid data-driven machine translation system containing core example-based components based on the marker hypothesis. OpenMaTrEx comprises a marker-driven chunker, a collection of chunk aligners, tools to merge (“hybridise”) marker-based and statistical translation tables, two engines —a simple proof-of-concept monotone “example-based” recom...
متن کاملGaijin: A Bootstrapping, Template- Driven Approach to Example-Based MT
Example-based Machine Translation (EBMT) is a recent approach to MT that offers robustness, scalability and graceful degradation, deriving as it does its competence not from explicit linguistic models of source and target languages, but from the wealth of bilingual corpora that are now available. Gaijin is such a system, employing statistical methods, string-matching, case-based reasoning and t...
متن کاملOpenMT: Open Source Machine Translation Using Hybrid Methods
The main goal of the OpenMT project is the development of open source machine translation architectures based on hybrid models and advanced syntactic–semantic processors. These architectures combine the three main Machine Translation (MT) frameworks, Rule-based (RBMT), Statistical (SMT) and Example–based (EBMT), into hybrid systems. Defined architectures and results will be open source, allow f...
متن کاملSelf-Organizing Machine Translation: Example-Driven Induction of Transfer Functions
Come, let us go down and there make such a babble of their language that they will not understand another's speech. { Genesis 11:7 With the advent of faster computers, the notion of doing machine translation from a huge stored database of translation examples is no longer unreasonable. This paper describes an attempt to merge the Example-Based Machine Translation (EBMT) approach with psycholing...
متن کاملKyotoEBMT System Description for the 1st Workshop on Asian Translation
This paper introduces the KyotoEBMT Example-Based Machine Translation framework. Our system uses a tree-to-tree approach, employing syntactic dependency analysis for both source and target languages in an attempt to preserve non-local structure. The effectiveness of our system is maximized with online example matching and a flexible decoder. Evaluation demonstrates BLEU scores competitive with ...
متن کامل