A method to detect the provisional boundaries of non-segmented kana sentences and its application

提出了一种利用音节的马尔可夫模型检测自然语音中包含的自修复串的方法。该方法包括两个步骤：第一步，确定具有自修复串的未切分音节句子的临时bunsetsu边界。我们对已提出的利用马尔可夫模型寻找正确句子的临时Bunsetsu边界的方法进行了改进，使之适用于具有自修复能力的句子。第二步是检测自修复字符串，它被插入到bunsetsu边界的位置。在这个步骤中，我们提出了三种模式匹配的方法来检测这些字符串，并将该方法应用于ATR对话语料库中的自修复字符串的检测。实验结果表明，该方法能有效地检测出插入到bunsetsu边界上的自修复串。

This paper proposes a method to detect self-repair strings included in spontaneous speech by Markov models of syllables. These strings are assumed to be represented with syllable strings obtained correctly by acoustic processing.The method comprises the following two steps: The first step is to determine the provisional bunsetsu boundaries of a non-segmented syllable sentence with self-repair strings. We improved the method which has been proposed to find the provisional bunsetsu boundaries of correct sentences by Markov models, to be applicable to sentences with self-repair. The second step is to detect self-repair strings, which are inserted in the location of bunsetsu boundaries. In this step, we proposed three methods of pattern matching to detect these strings.This method is applied to detect self-repair strings in ATR dialogue corpus. It is confirmed that the method is effective to detect self-repair strings inserted in bunsetsu boundaries.