MateCat aims at improving the integration of machine translation and human translation within the so-called computer aided translation (CAT) framework.
CAT tools represent nowadays the dominant technology in the translation industry. They provide translators with text editors that can manage several document formats and suitably arrange their content into segments — i.e. sentences –, ready to be translated. Most importantly, CAT tools provide access to dictionaries, to translation memories (TMs), and more recently to machine translation (MT) engines. A TM is basically a repository of translated segments. During translation, the CAT tool queries the TM to search for exact or fuzzy matches of the current source segment. These matches are proposed to the translator as translation suggestions. Once a segment is translated, its source and target texts are added to the TM for future queries. Recently, when no good matches are found in the TM, suggestions from an MT engine are also supplied to the translator.
Recent studies have shown that post-editing suggestions from a statistical MT engine can substantially improve productivity of professional translators. MateCat leverages the growing interest and expectations in statistical MT by advancing the state of the art along directions that will hopefully accelerate its adoption by the translation industry. In particular, MateCat is investigating the integration of MT into the CAT working process along three main research directions:
- Self-tuning MT, i.e. methods to train statistical MT engines for specific domains or translation project;
- User adaptive MT, i.e. methods to quickly adapt statistical MT from user corrections and feedback.
- Informative MT, i.e. supply users with additional information to enhance their productivity and work experience.
These new features have been integrated in a new Web-based CAT tool: the MateCat Tool. The MateCat Tool provides both a professional work environment integrating enhanced MT and a research platform to run post-editing experiments and to measure user productivity.
Progress in MateCat is systematically measured through field tests evaluating the utility and usability of the new MT features. Field tests are run with professional translators performing real translation projects with the MateCat Tool.