Referring expression generation using speaker-based attribute selection and trainable realization (ATTR)
Giuseppe Di Fabbrizio, Amanda J. Stent, Srinivas Bangalore · 2008
In the first REG competition, researchers proposed several general-purpose algorithms for attribute selection for referring expression generation. 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.