A Statistical Approach to Thai Morphological Analyzer

Three nontrivial problems of Thai morphological processing are word boundary ambiguity, tagging ambiguity and implicit spelling errors. These problems cause a lot of difficulty to the parser due to the alternative or erroneous chain of word. This work attempts to provide a computational solution, called Word Filtering, to those linguistic phenomena. The filtering process calculates the probabilities of all possible chains of tagged words using a Markov Model. The most likely sequence of tagged word is the one that maximizes the chain probabilities. However, it may be an erroneous chain which has an implicit spelling error. Therefore, the Word Filtering, also, includes the scanning process that detect and correct these errors. Both filtering and scanning process use a statistical data infonuation collected ~om the hand-ta.~ed corpus. The experiment has shown that word filtering can eliminate most of the alternative word sequences. Moreover: this tcelmique is fairly good at the implicit error correction.