A maximum entropy approach for spoken Chinese understanding

Authors:
Guodong Xie;Chengqing Zong;Bo Xu
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing
Venue:
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Year:
2003

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Abstract

In this paper, we present a spoken language understanding method based on the maximum entropy model. We first extract certain features from the corpus, and then train the maximum entropy model with an annotated corpus. We use this model to analyze spoken Chinese into semantic frames. Experiments show that the model can work effectively.