Trainable Speaker-Based Referring Expression Generation.
CoNLL '08: Proceedings of the Twelfth Conference on Computational Natural Language Learning(2008)
摘要
Previous work in referring expression generation has explored general purpose techniques for attribute selection and surface realization. However, most of this work did not take into account: a) stylistic differences between speakers; or b) trainable surface realization approaches that combine semantic and word order information. In this paper we describe and evaluate several end-to-end referring expression generation algorithms that take into consideration speaker style and use data-driven surface realization techniques.
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关键词
data-driven surface realization technique,surface realization,trainable surface realization approach,expression generation,expression generation algorithm,previous work,attribute selection,consideration speaker style,general purpose technique,stylistic difference
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