Improving the generation of personalised descriptions
Thiago Castro Ferreira, Ivandré Paraboni · 2017
Referring expression generation (REG) models that use speaker-dependent information require a considerable amount of training data produced by every individual speaker, or may otherwise perform poorly.In this work we propose a simple personalised method for this task, in which speakers are grouped into profiles according to their referential behaviour.Intrinsic evaluation shows that the use of speaker's profiles generally outperforms the personalised method found in previous work.