Automatic modification of communication style in dialogue management

Comunicació presentada a: INLG 2016 Workshop on Computational Creativity and Natural Language Generation, celebrat a Edinburgh, Escòcia, del 5 al 8 de setembre de 2016.In task-oriented dialogues, there is often only one right answer the system can give. However, a lack of variation can seem repetitive and unnatural. Humans change the way they express something, e.g. by being more or less concise. We aim to approximate this ability by automatically varying the level of verbosity and directness of a given system action. In this work, we illustrate how verbosity and directness may be utilised in adaptive dialogue management and present different approaches to automatically generate varying levels of verbosity and directness for given system actions. Thereby, new and unforeseen system actions can be created dynamically.This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 645012

Automatic modification of communication style in dialogue management

Comunicació presentada a: INLG 2016 Workshop on Computational Creativity and Natural Language Generation, celebrat a Edinburgh, Escòcia, del 5 al 8 de setembre de 2016.In task-oriented dialogues, there is often only one right answer the system can give. However, a lack of variation can seem repetitive and unnatural. Humans change the way they express something, e.g. by being more or less concise. We aim to approximate this ability by automatically varying the level of verbosity and directness of a given system action. In this work, we illustrate how verbosity and directness may be utilised in adaptive dialogue management and present different approaches to automatically generate varying levels of verbosity and directness for given system actions. Thereby, new and unforeseen system actions can be created dynamically.This paper is part of a project that has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 645012