Two Language Models Using Chinese Semantic Parsing

作     者：李明琴 王侠 王作英 

作者机构：Department of Electronic Engineering Tsinghua University 

出 版 物：《Tsinghua Science and Technology》 (清华大学学报（自然科学版（英文版）)

年 卷 期：2006年第11卷第5期

页      面：582-588页

核心收录：

学科分类：0501[文学-中国语言文学] 0303[法学-社会学] 050102[文学-语言学及应用语言学] 03[法学] 030303[法学-人类学] 05[文学] 

基　　金：Supported by the National High-Tech Research and Development (863) Program of China (No. 2004AA114011-2) 

主　　题：language model semantic parsing dependency grammar speech recognition 

摘      要：This paper presents two language models that utilize a Chinese semantic dependency parsing technique for speech recognition. The models are based on a representation of the Chinese semantic structure with dependency relations, A semantic dependency parser was described to automatically tag the semantic class for each word with 90.9% accuracy and parse the sentence semantic dependency structure with 75.8% accuracy. The Chinese semantic parsing technique was applied to structure language models to develop two language models, the semantic dependency model （SDM） and the headword trigram model （HTM）. These language models were evaluated using Chinese speech recognition. The experiments show that both models outperform the word trigram model in terms of the Chinese character recognition error rate.