Msc Projects

This page holds proposals for Master graduation projects within the II group. If you are interested in one of these projects, please contact the listed staff member for more information or to set up a meeting. It is typiically also possible to do a masters project on one of the research projects in this group, which might not have a specific assignment on this page. Take a look at the Research page to see other possible topics, and who to contact in those cases.
 

Memorability of conversations and prosody

EEMCS Master’s Project Open-Call

Prosody has been long known to affect our perception of speech. It's tough to concentrate on a monotonic lecture. On the other hand, a lecturer with varying prosody is more comfortable to follow. An engaging speaker helps their listeners keep alert and memorise the speech's content (Strangert & Gustafson 2008) by stressing the critical words, pausing when needed, and expressing excitement about the topic. The relation between prosody and short-term memory has been studied extensively (e.g. Rodero 2015) as has the relationship to syntactic difficulty (Rosner et al. 2003). However, these studies did not investigate the effect on long-term memory and didn't differentiate between different information types. In conversational agents research, prosody has been shown to increase user overall engagement and satisfaction (Chaoi & Agichtein 2020), but the question of memory facilitation seems to remain uncovered. In this thesis project, you will investigate whether prosody affects the long-term memorisation of the information communicated by a conversational agent. Another question that can be asked is memorisation of what kind of information gets affected by prosody the most.

Supervision: Catharine Oertel, Maria Tsfasman, Interactive Intelligence

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Memorability of conversations: factors and automatic prediction

EEMCS Master’s Project Open-Call

Humans have a selective memory. They are good at capturing the most critical moments ofa conversation but are generally incapable of remembering every detail. One way in whichartificial agents can become more socially-aware is by modelling how humans rememberconversations. The first step towards understanding how humans choose what to rememberis by studying the human encoding process and more explicitly how sensory information isfiltered and stored in memory. Memorability has been studied from a computer vision pointof view [3, 4] also investigating multimodal aspects [1]. However, in these studies, aconversational setting has widely been ignored.

Supervision: Catharine Oertel, Maria Tsfasman, Interactive Intelligence

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Lying to Robots: Social AI Deception Awareness & Deterrence

EEMCS Bachelor’s & Master’s Project Open-Call

What should robots do when they are being lied to? Join us in investigating computational models for handling human deception. As AI agents become more prevalent, it is paramount that we design for a human propensity for exploiting and corrupting these systems.

In this project, you will design, develop, and test mechanisms (protocols and modalities) for AI agents within AI-human interaction where the human party is incentivised to be dishonest. You will work with PhDs within Designing Intelligence Lab to develop a framework for detecting and a library of mechanisms deterring deception through conversational interfaces.

Supervision: Catharine Oertel, Eric (Heng) Gu, Interactive Intelligence

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Teach Conversational AI to play Tabletop Games through Active Learning

EEMCS Bachelor’s & Master’s Project Open-Call

AI can play games; it can even beat the best human players. There has been a torrent of successful deep reinforcement learning applications in digital games (Go, Dota, Atari games, etc). With time and a well-designed reward system, agents can quickly develop strategies to play the game effectively. However, we are not interested in simply spectating how well an AI agent can play one game, after hours of training. We want one that we can teach to play any game with us, right out the box.

In this project, you will build a conversation AI framework employing active learning to grasp a non-digital game's gameplay and quickly reach "enough competency" to play with any human partner(s). You will work with PhD candidates within the Designing Intelligence Lab to develop semi-supervised machine learning algorithms. You will apply NLU in a tabletop gameplay meta-learning context.

Supervision: Catharine Oertel, Eric (Heng) Gu, Interactive Intelligence

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Developing Conversational AI for Design Settings: how to use conversational agents for increasing your creativity

EEMCS Master’s Project Open-Call

Creativity and innovative thinking are highly desired skills in today's society individually and also in the context of teamwork. One essential part of creativity is idea generation where people explore a given problem's solution space. The most known techniques for idea generation include generating ideas from memory and by direct association (inventory and association), identifying and breaking common assumptions (provocative) or using analogies (confrontative). In human-human interaction, these process, however, is often burdened by social factors such as criticism, dominance, judgment, comparison - to name a few. Could technology help here?

Supervision: Catharine Oertel, Joanna Mania, Interactive Intelligence

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