An Improved Indonesian Grapheme-to-Phoneme (G2P) Conversion using Statistic and Linguistic Information

A research paper by Agus Hartoyo and Suyanto

This paper focuses on IG-tree + best-guess strategy as a model to develop Indonesian grapheme-to-phoneme conversion (IndoG2P). The model is basically a decision-tree structure built based on a training set. It is constructed using a concept of information gain (IG) in weighing the relative importance of attributes, and equipped with the best-guess strategy in classifying the new instances. It is also leveraged with two new features added to its pre-existing structure for improvement. The first feature is a pruning mechanism to minimize the IG-tree dimension and to improve its generalization ability. The second one is a homograph handler using a text-categorization method to handle its special case of a few sets of words which are exactly the same in spelling representations but different each other in phonetic representations. Computer simulation showed that the complete model performs well. The two additional features gave expected benefits.


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