Knowledge-based grapheme-to-phoneme conversion of Lithuanian words

This paper presents a knowledge-based approach to grapheme-to-phoneme conversion (G2P) of isolated words of Lithuanian. Grapheme-to-phoneme conversion is performed in three consecutive steps: syllable boundary identification, accentuation, and transcription. Automatic accentuation is the most challenging task that is solved by combining lexicon with the accentuation rules formalized for every grammatical category. The algorithm is evaluated on the list of 50 000 word types which is obtained by selecting 100 most frequent word types per grammatical category. The proposed algorithm achieved 93.5% and 98.9% G2P accuracy at word and grapheme level respectivelyVytauto Didžiojo universiteta