The purpose of this project is to gain a better understanding of human-human dialogue through formal/computational modelling (Piwek, 2011; 2006). It will focus one of the following three phenomena in dialogue:

1. multimodal dialogue acts (involving gesture and speech) (Piwek 2009; Piwek, Beun & Cremers, 2008),
2. generation of questions (Piwek & Boyer, 2012; Kuyten et al., 2012; Rus et al. 2010; Wyse & Piwek, 2009), or
3. adversarial dialogue moves (and emotion) (Pluss, 2014; Pluss, Piwek & Power, 2011).

The main aim of the project will be to construct a computational model of one of these phenomena. This will involve building algorithms for automatically generating dialogue acts that exhibit the relevant phenomenon (for example, a model for automatically generating questions or, for instance, for generating multimodal dialogue acts).

The research may (or may not) involve developing a pair of agents that have the ability to converse with each other, with the resulting behaviour mirroring, in relevant respects, the human behaviours as we find them in naturally-occurring dialogues.

Skills and Background required

A good undergraduate degree (2.1 or above) in Computing (or equivalent), with experience in artificial intelligence, computational linguistics or natural language processing. A background in linguistics would also be suitable, if accompanied by a suitable computer skills.

References

In a number of books (e.g. Brandom, 1994; Brandom, 2000), the philosopher Robert Brandom has uncovered deep connections between dialogue games and argumentation on the one hand, and meaning on the other. Some progress has been made on making these ideas computational (see e.g. Piwek, 2014). The aim of this project is to further develop and implement these computational interpretations of Brandom's work. This may include the use of visualisations in order to get a better understanding of the models. It could also lead to development of applications (e.g., in argumentation education).

Skills and Background required

A good undergraduate degree (2.1 or above) in Computing (or equivalent), with experience in logical semantics (ideally, also proof-theoretic/inferentialist approaches) and/or dialogue modelling.

References

Companies, governments and citizens produce and share data on a wide variety of topics. In order to make productive and informed use of such data, they needs tools and technologies to explore these data. In particular, they could benefit from help with articulating questions that the data may address and with discovering possible stories that the data is (or perhaps isn't) telling.

We propose to use AI techniques and text generation to allow users to engage with data. For instance, the proposed technology could suggest possible questions or stories based on the data. We will focus on inclusive technologies, e.g. by linking up text generation with spoken language technologies to ensure accessibility for visually-impaired users.

We propose to use AI techniques and text generation to allow users to engage with data. For instance, the proposed technology could suggest possible questions or stories based on the data. We will focus on inclusive technologies, e.g. by linking up text generation with spoken language technologies to ensure accessibility for visually-impaired users.

Skills and background

Good undergraduate degree (2.1 or above) in Computing, ideally with experience in natural language processing.

References