Improved prediction of Japanese word accent sandhi using CRF

要旨

In Japanese, every content word has its own mora-based H/L pitch pattern when it is uttered in isolation, called accent type. When reading out a written sentence, however, this lexical H/L pattern is often changed according to the context, known as word accent sandhi. In our previous work, an accent sandhi predictor was developed using CRF [1], and in this paper, the predictor is improved through feature engineering especially fo-cusing on phrases including numerals and those including loan-words. This is because our previous work showed that the pre-diction performance was relatively low for those phrases. To optimize the features used for CRF, it is critical to take into ac-count the mechanism of word accent sandhi. We review linguis-tic and technical literature that attempted to characterize accent sandhi in the phrases including numerals and loanwords and, by reflecting these characteristics, the features are re-designed. Experiments show that the proposed predictor improved the per-formance relatively by 37 % and 41%, respectively. Index Terms: word accent sandhi, accent nucleus, text-to-speech, Japanese education, rule-based, corpus-based, CRF

主題