A linguistically motivated approach to grapheme-to-phoneme conversion for Korean

This paper describes a hand-written rule-based grapheme-to-phoneme (GTP) conversion system for Korean built within the Festival text-to-speech (TTS) synthesis framework. The core of the GTP conver-sion system is a simple implementation of nine linguistically motivated morphophonological rules. These rules, which are well known to students of Korean linguistics, were implemented in Festival rewrite formal-ism, and were applied to 1.3 million distinct orthographic words (space-delimited eojeols) from the Korean Newswire corpus. The outputs were evaluated against a representative subset of eojeols. The subset was examined by three native speakers of Korean, who judged 91.17 % of the word types in a stratified sample of Korean eojeols to be acceptable pronunciations, which means that our system converted 99.63 % of the grapheme tokens correctly. This performance is comparable to that obtained from earlier studies such as Kim et al. [Morpheme-based grapheme to phoneme conversion using phonetic patterns and morphopho-nemic connectivity information. ACM Transactions on Asian Language Information Processing 1 (1) (2002) 65–82] which, contrary to our system, used an elaborate morphological analysis module. This is evi-dence of the potential benefit of well-abstracted linguistic knowledge. In addition, because our approach is based on well-known linguistic principles, error analysis is fairly straightforward. Straightforward error analysis is an essential step in knowing what features are likely to be informative in training a hybrid system where exceptions to rules are handled by a machine-learning component. 2005 Published by Elsevier Ltd. 0885-2308/ $- see front matter 2005 Published by Elsevier Ltd. doi:10.1016/j.csl.2005.03.002 * Corresponding author