English-Lithuanian-English Lexicon Database Management System for MT Gintaras Barisevicius and Elvinas Cernys Kaunas University of Technology, Department of Software Engineering Singleton Labs.

2 Situation in Lithuania

3  General electronic dictionaries  Morphological analysis tools  Text corpora (100 mln. words)  Speech recognition systems  Machine translation research

4 Previous dictionary  Open to the user dictionary  Rigid dictionary structure  Lack of attributes  Not all parts of speech included  Indexed files for dictionary storage  Polysemy not included  Phrases not included

5 Requirement to new system  Open to the user dictionary  Easy management of the attributes  All parts of speech  Big volume storage  Solution to polysemy and synonyms

6 Project size

7 Current system  Orientated to MT  More attributes, easy to extend  All parts of speech included  Database for dictionary storage  Polysemous words, domains  Automatic generation of morphological forms  System can work on various OS.

8 Development process  From C++ to Java  Rational Rose tool  CVS for version control management  MySql database

9 Adding new languages

10 System deployment localy

11 System deployment online

12 Future ambitions  Phrases  Text corpora  Syntax rule realization  Additional features Possible other translation choices WEB translation Video subtitle translation

13 Text corpora usage in MT  The pen is on the table. PEN TABLE RASIKLIS STALAS LENTELE Look usage with RASIKLIS RASIKLIS usage with STALAS is more often!

14 Conclusions  Thorough analysis of Lithuanian and English language conducted  Additional features to the dictionary have to be added (phrases, syntax rules)  Filling the dictionary can be started  Machine translation is underway

15 Thank you for your attention. Gintaras Barisevicius