  In Japanese text-to-speech (TTS), it is necessary to add accent information
to the input sentence. However, there are a limited number of publicly
available accent dictionaries, and those dictionaries e.g. UniDic, do not
contain many compound words, proper nouns, etc., which are required in a
practical TTS system. In order to build a large scale accent dictionary that
contains those words, the authors developed an accent estimation technique that
predicts the accent of a word from its limited information, namely the surface
(e.g. kanji) and the yomi (simplified phonetic information). It is
experimentally shown that the technique can estimate accents with high
accuracies, especially for some categories of words. The authors applied this
technique to an existing large vocabulary Japanese dictionary NEologd, and
obtained a large vocabulary Japanese accent dictionary. Many cases have been
observed in which the use of this dictionary yields more appropriate phonetic
information than UniDic.
