Automatic Generation of Personalised and Context-Dependent Textual Interventions During Neuro-rehabilitation

Abstract

In this paper we present our system that synthesises personalised and context dependent texts during robot guided exercises for neuro-rehabilitation. This system is used to generate texts for the communication between a care robot and patients. We present requirements that a system in such a medical domain has to meet. Afterwards the results of a systematic literature review are presented. We present our solution based on the RosaeNLG system. It supports different language levels and referring expressions in a real-time text generation system, so that generated texts can be adapted to the reader in the best possible way. We evaluate our system with respect to the requirements. The contribution of the paper is twofold: We present a set of requirements for Natural Language Generation (NLG) in medical domains and we show how to extend RosaeNLG with an external dialogue memory to handle complex referring expressions in medical real time settings.