Grapheme-to-Phoneme Conversion Using Automatically Extracted Associative Rules for Korean TTS System

In this paper, we describe a method for automatically extracting grapheme-to-phoneme conversion rules directly from the transcription of speech synthesis database and introduce a weighted score and jamo similarity to overcome the rule application difficulties. We make a structured rule tree by rule pruning and rule association, and can eliminate most of the rules with almost no decrease of the performance. Our system achieves over 99.5 percent of phoneme-level accuracy and this performance is easily achievable even with the small amount of training data.