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

本文提出了一种利用音节马尔可夫模型检测自发语音中包含的自修复字符串的方法。这些字符串被认为是由声学处理正确获得的音节字符串表示的。该方法包括以下两个步骤：第一步是确定具有自修复字符串的非分段音节句子的临时词集边界。我们改进了已经提出的用马尔可夫模型寻找正确句子的临时bunsetsu边界的方法，使其适用于具有自我修复功能的句子。第二步是检测自修复字符串，这些字符串插入到bunsetsu边界的位置。在这一步中，我们提出了三种模式匹配方法来检测这些字符串。将该方法应用于ATR对话语料库中的自修复字符串检测。实验结果表明，该方法能够有效地检测插入帧边界的自修复字符串。

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.