Word Sense Disambiguation of Spoken Chinese Using Neural Network
基于神经网络的汉语口语多义选择

Spoken Chinese analysis lies in the center of interactive speech processing system.The smallest meaningful unit in Chinese language is the word,so word sense disambiguation is the basis of spoken Chinese analysis.In this paper, the authors propose a novel method for spoken Chinese word sense disambiguation based on a simple recurrent network. This method provides a consistent processing strategy for syntax and semantics according to the internal logic between the word syntactic classification and semantic classification. Applied in the corpus for meeting schedule, this method achieves an accuracy of 96.9% in an open testing of word sense disambiguation.