Detecting errors in Chinese spoken dialog system using ngram and dependency parsing

摘要：

In this paper, a hybrid method of detecting ASR error in spoken turns is developed. The erroneous text is locally analyzed first by neighbouring co-occurrence relations using ngram model. Then the text is globally analyzed by long distance dependency relations using a dependency parser. Our experiments show that we can use information from a dependency parsing phase together with n-gram language model not only to detect erroneous ASR hypotheses that can cause understanding errors, but also reliably locate errors and sometimes correct them as the hypotheses are being processed.

关键词： Detecting errors N-gram Dependency parsing Spoken dialog system

作者: Weidong ZHOU Baozong YUAN Zhenjiang MIAO Weibin ZHU Weibin LIU

作者单位: Institute of Information Science,Beijing Jiaotong University,Beijing 100044,P.R.China;College of Inf Institute of Information Science,Beijing Jiaotong University,Beijing 100044,P.R.China

会议类型: 国际会议

会议名称: The IET 2nd International Conference on Wireless,Mobile & Multimedia Networks(第二届IET国际无线移动多媒体网络会议)

会议地点: 北京

会议语种:英文

在线出版日期: 2008-10-12（万方平台首次上网日期，不代表论文的发表时间）