This paper proposes a new model of machine translation system in which rule-based and example-based
approaches are applied for English-to-Thai sentence translation. The proposed method has 4 steps :1)
analyze an English sentence into a string of grammatical nodes, based on Phrase Structure Grammar, 2)
map the input pattern with a table of English-Thai sentence patterns, 3) look up the bilingual dictionary for
the equivalent Thai words, reorder and then generate output sentences and 4) rank the possible
combinations and eliminate the ambiguous output sentences by using a statistical method. The translated
sentences will then be stored in a bilingual corpus to serve as a guide or template for imitating the
translation, i.e., the example-based approach. The future work will focus on disambiguation by using
semantic features to make a more precise translation.
1. INTRODUCTION
Various efforts have been made in developing machine translation (MT) systems for practical
This paper proposes a new model of machine translation system in which rule-based and example-based
approaches are applied for English-to-Thai sentence translation. The proposed method has 4 steps :1)
analyze an English sentence into a string of grammatical nodes, based on Phrase Structure Grammar, 2)
map the input pattern with a table of English-Thai sentence patterns, 3) look up the bilingual dictionary for
the equivalent Thai words, reorder and then generate output sentences and 4) rank the possible
combinations and eliminate the ambiguous output sentences by using a statistical method. The translated
sentences will then be stored in a bilingual corpus to serve as a guide or template for imitating the
translation, i.e., the example-based approach. The future work will focus on disambiguation by using
semantic features to make a more precise translation.
1. INTRODUCTION
Various efforts have been made in developing machine translation (MT) systems for practical
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