B. Hettige

A Parser for Sinhala Language - First Step Towards English to Sinhala Machine Translation

Sinhala language parser has been developed as the first step towards English to Sinhala natural language translation. The Sinhala parsing system comprises of a Sinhal a morphological analyzer that connects with three dictionaries, namely, base dictionary, rule dictionary and concept dictionary. The morphological analyzer of the parsing system implements inflection and derivation rules of the Sinhala grammar, and provides grammatical information of the words to be considered by the parser. The current version of the parser is capable of handling simple and complex sentences of Sinhala language. The entire system has been developed using Java and SWI-Prolog that runs on both Linux and Windows

A Morphological Analyzer to Enable English to Sinhala Machine Translation

Morphological analysis plays a key role in effective functioning of a parser of any machine translation system. Further, morphological analyzers are useful as supportive software tools to coin terms for a given language. This paper reports on the first morphological analysis system for Sinhala language. This comes out as a major step in the development of a Sinhala parser for machine translation from English to Sinhala. The paper describes how the morphological analyzer can detect grammatical information of a given Sinhala word, and generation of all possible forms of the given word. It is also presented how a language specialist can use our system to device Sinhala terms that are agreeable with Sinhala grammar. The system has been developed with the use of SWI-Prolog, and to runs on Windows and Linux.

Developing lexicon databases for English to Sinhala machine translation

Machine translation has been identified as one of the most challenging areas in natural language processing. In such systems, lexicon databases are fundamental to handle all translation requirements including lexicon, syntax and semantics information. This paper reports on the design and development of a lexicon database sub-system for English to Sinhala machine translation system. This system has customized the famous WordNet for English lexicon database, and structured three Sinhala dictionaries as per Japanese EDR system. SWI-Prolog has been used for the development of the core of the translation system.

Transliteration system for English to Sinhala machine translation

Machine translation is a challenging task in natural language processing. Out-of-vocabulary, handling proper nouns and technical terms are some major issues which are common to all machine translation systems. This paper presents a transliteration approach to machine translation from English to Sinhala. We have used finite state automaton to develop transducers for English to Sinhala transliteration. This approach can transliterate the text in original English and Sinhala words that are written using English letters. The transliteration system has been developed using SWI-PROLOG and prolog server page (PSP). English WorldNet and Sinhala Chatbot are used to test the transducers and reasonable results were achieved.

An evaluation methodology for English to Sinhala machine translation

This paper presents evaluation methodology for English to Sinhala machine translation system. The English to Sinhala machine translation system has been developed by using Multi Agent Approach and powered through the concept of “Varanegeema”. Translation system works through the communication among nine agents namely English Morphological Analyzer Agent, English Parser Agent, English to Sinhala Base Word Translator Agent, Sinhala Morphological Generator Agent, Sinhala Parser agent, Transliteration agent, Intermediate Editor agent, Message Space Agent and Request agent. The evaluation was conducted through three steps. As the first step, evaluation was conducted through the white box testing approach and tested each module in the machine translation system through the developed testing tools. Then, evaluated the system performance and calculated the error rate through the result of the evaluation test bed. Finally, Intelligibility and the Accuracy test will be conducted through the human support. The experimental result shows 89% accuracy of the overall system and 7.2% word error rate and the 5.4% sentence error rate. Details of the evaluation and results are given in the paper

Theoretical based approach to English to Sinhala machine translation

Machine translation is a log felt need of the countries those who use English as a second language. Due to inherent complexity of natural languages, most of machine translation systems adopt rather ad-hoc strategies such as word level translation without concerning a proper theoretical basis. This has been a major reason for why the developments in natural language processing could not achieve as expected. This paper presents a theoretical-based approach to English-Sinhala machine translation through the concept of Varanagema (conjugation) in Sinhala Language. The theory of Varanagema in Sinhala language handles major language primitives including noun, verbs and prepositions. The concept of Varanagema also drastically reduces the number of word forms to be stored in the dictionaries of the machine translation system. The design, implementation and results of test versions of English-Sinhala machine translation system has been presented in the paper.

Web-based English-Sinhala translator in action

Machine translation has been a potential solution for addressing the language barrier. In line with this, we have developed English to Sinhala machine translation system that can be accessed through the Internet. The translation system runs on a Web sever and can be accessed by an ordinary Web client. The core of the translation system contains seven modules, namely, English Morphological analyzer, English parser, Translator, Sinhala Morphological generator, Sinhala parser, Transliteration module and three Lexicon Databases. This core system has already been tested and used on standalone machines. The current project has extended the core system with the use of Prolog Server Pages to provide online access thereby opening the service to a wider audience.