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Two Language Models Using Chinese Semantic Parsing

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【作者】 李明琴王侠王作英

【Author】 LI Mingqin , WANG Xia, WANG Zuoying Department of Electronic Engineering, Tsinghua University, Beijing 100084, China

【机构】 Department of Electronic Engineering Tsinghua UniversityDepartment of Electronic Engineering Tsinghua UniversityBeijing 100084 China Beijing 100084 China Beijing 100084 China

【Abstract】 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 struc- ture with dependency relations. A semantic dependency parser was described to automatically tag the se- mantic 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.

【基金】 Supported by the National High-Tech Research and Development (863) Program of China (No. 2004AA114011-2)
  • 【文献出处】 Tsinghua Science and Technology ,清华大学学报(自然科学版英文版) , 编辑部邮箱 ,2006年05期
  • 【分类号】H030
  • 【被引频次】2
  • 【下载频次】32
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