Sascha Griffiths

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The present contribution investigates the construction of dialogue structure for the use in human-machine interaction especially for robotic systems and embodied conversational agents. We are going to present a methodology and findings of a pilot study for the design of task-specific dialogues. Specifically, we investigated effects of dialogue complexity on(More)
We propose an approach for the representation of actions based on the conceptual spaces framework developed by Gärdenfors (2004). Action categories are regarded as properties in the sense of Gärdenfors (2011) and are understood as convex regions in action space. Action categories are mainly described by a force signature that represents the forces that act(More)
A model is proposed showing how automatically extracted and manually written association rules can be used to build the structure of a narrative from real-life temporal data. The generated text’s communicative goal is to help the reader construct a causal representation of the events. A connecting associative thread allows the reader to follow associations(More)
This publication can be cited as: Dafydd Gibbon, Firmin Ahoua, Blé François Kipré & Sascha Griffiths. 2009. Discrete level narrative, terraced music: insights from underdocumented Ivorian languages. In Peter K. Austin, Oliver Bond, Monik Charette, David Nathan & Peter Sells (eds) Proceedings of Conference on Language Documentation and Linguistic Theory 2.(More)
Advancements in Human-Robot Interaction involve robots being more responsive and adaptive to the human user they are interacting with. For example, robots model a personalised dialogue with humans, adapting the conversation to accommodate the user's preferences in order to allow natural interactions. This study investigates the impact of such personalised(More)
Similarity is a core notion that is used in psychology and two branches of linguistics: theoretical and computational. The similarity datasets that come from the two fields differ in design: psychological datasets are focused around a certain topic such as fruit names, while linguistic datasets contain words from various categories. The later makes humans(More)