PREDICTING PROSODIC WORDS FROM LEXICAL WORDS--A FIRST STEP TOWARDS PREDICTING PROSODY FROM TEXT

摘要

Much remains unsolved in how to predict prosody from text for unlimited Mandarin Chinese TTS. The interactions and the governments between syntactic structure and prosodic structure were still unresolved challenges. By using Part-of-Speech tagging (hence POS), lexical information of text was required, we aimed to find significant patterns of word grouping from analyzing real speech data and such lexical information. This paper reported discrepancies found between lexical words (hence LW) parsed from text and prosodic words (hence PW) annotated from speech data, and proposed a statistical model to predict PWs from LWs. In statistical model, both length of the word and the tagging from POS are two essential features to predict PWs, and the results showed approximately 90% of prediction for PWs, however, it did leave more room for extension. We believe that evidence from PW predictions is a first step towards building prosody models from text.