I'm Aislinn (she/her).
[æʃliːn kiːoʊ]
I'm a PhD student in the Centre for Language Evolution at the University of Edinburgh, supervised by Professor Jennifer Culbertson and Professor Simon Kirby. I use behavioural experiments and computational modelling to study the evolution of linguistic structure.
Fundamentally, I'm interested in how the cognitive demands associated with real-time language processing and production might affect the organisational structure of linguistic systems. Questions I'm trying to answer include:
- What kinds of pressures and biases operating during language production might help explain cross-linguistic regularities?
- How do languages achieve an optimal trade-off when production biases pull in different directions from those operating during comprehension or learning?
- To what extent do these kinds of biases vary between individuals, and does this individual variation affect the trajectory of language evolution?
My research is funded by the Scottish Graduate School of Social Science (an ESRC doctoral training programme).
Before my PhD, I did an MSc in Evolution of Language and Cognition, also at the University of Edinburgh (2020-21). I received my bachelor's degree in Linguistics from Newcastle University in 2013. In the intervening period, I was working in higher education policy and public sector communications.
Projects
The evolution of phonetic clustering in the lexicon
Cross-linguistically, lexicons tend to be more phonetically clustered than required by their phonotactics; that is, words are more similar to each other than they need to be. In this project, I am interested in how this property might arise from a trade-off between competing pressures from language production (which generally favours similarity) and comprehension (which generally favours distinctiveness). To find out more, you can read an abstract from the 2024 AMLaP conference or see the poster I gave at the 2024 CogSci conference.
Working memory and the regularisation of linguistic variation
Regularisation is a well-documented process whereby languages become less variable (on some dimension) over time. This process has been argued to be driven by the behaviour of individual language users, but the specific mechanism is not agreed upon. In this project, I tested whether limitations in working memory during either language learning or language production drive regularisation behaviour. To find out more, you can read my paper in Cognitive Science.
Task effects in morphological rule learning
There is good evidence that language learning is boosted by engaging in more active production tasks, compared to more passive comprehension tasks. However, adult learners do not acquire all kinds of linguistic rules equally well; in particular, morphological rules like case marking pose a significant challenge. In this collaborative project with my colleague Elizabeth Pankratz, we investigate whether the type of task learners use to practise a new language can affect the kinds of rules they acquire. To find out more, you can read our preprint.
Individual differences in learning from redundant linguistic cues
Redundancy is ubiquitous in the world's languages, but its functions are not yet well understood. In this collaborative project with Professor Gary Lupyan at the University of Wisconsin-Madison, we propose that redundancy might make language more robust to individual differences in learning, since it means that different learners can rely on different cues to acquire the same underlying structure. To find out more, you can read our paper in the proceedings of the 2024 Evolang conference.
Publications
Keogh, A., Kirby, S., & Culbertson, J. (2024). Predictability and variation in language are differentially affected by learning and production. Cognitive Science, 48(4), e13435 [URL] [PDF]
Pankratz, E., Keogh, A., Kirby, S., & Culbertson, J. (2024). For learning morphological rules, production tasks are no better than comprehension. OSF Preprints [URL] [PDF]
Keogh, A., & Pankratz, E. (2024). Simulation as a tool for formalising null hypotheses in cognitive science research. Proceedings of the Annual Meeting of the Cognitive Science Society, 46 [URL] [PDF]
Keogh, A., & Lupyan, G. (2024). Who benefits from redundancy in learning noun class systems? The Evolution of Language: Proceedings of the 15th International Conference (Evolang XV) [URL] [PDF]
Keogh, A., Kirby, S., & Culbertson, J. (2022). In search of a unified mechanism for regularisation of linguistic variation. Proceedings of the 23rd Amsterdam Colloquium, 360-366 [URL] [PDF]