Vowel Sound Disambiguation for Intelligible Korean Speech Synthesis

For speech synthesis systems that transform text materials into voice data, correctness and naturalness are the crucial measures of performance, the latter gaining more emphasis recently. In order to make synthesized voices natural, we must take into account pronunciation-related linguistic phenomena such as homograph, among others. The syntax certainly provides an important clue to disambiguating such homographs, but the relatively free word order in the Korean language makes it hard to utilize such information. In this paper, we describe a computational generation of contextually appropriate vowel lengths for the words in Korean by utilizing a higher level of linguistic information in a Combinatory Categorial Grammar framework. We consider parts-ofspeech information, the possibility of conjunction with a suffix, case information, unconjugated adjectives, numerals, numerical adjectives with related nouns, and the relationship between a noun and its predicate as syntactic and semantic clues for vowel sound disambiguation. The results are expressed in Speech Synthesis Markup Language (SSML) for a target system neutral application. The proposed system with correctly predicted vowel sound can be used not only as an educational tool, but also as a plug-in for enhancing the intelligibility of a general purpose Text-to-Speech (TTS) system.