Thursday, 18th April - 11am Guy Emerson : Seminar Title: Truth conditions at scale, and beyond Abstract: Truth-conditional semantics has been successful in explaining how the meaning of a sentence can be decomposed into the meanings of its parts, and how this allows people to understand new sentences. In this talk, I will show how a truth-conditional model can be learnt in practice on large-scale datasets of various kinds (textual, visual, ontological), and how this provides empirical benefits compared to non-truth-conditional models. I will then take stock of the bigger picture, and argue it is (unfortunately) computationally intractable to reduce all kinds of language understanding to truth conditions. To enable a more complete account, I will sketch a new approach to approximate Bayesian modelling, with the potential to explain how patterns of language use arise as a result of resource-bounded minds interacting with a computationally demanding world. Bio: Guy Emerson is a computational semanticist at the University of Cambridge. He pursues research as an academic fellow at the Department of Computer Science & Technology, pursues teaching as a college lecturer at Gonville & Caius College, and promotes interdisciplinary work as an executive director of Cambridge Language Sciences. He also supports revitalisation of the Hokkien language, and enjoys ballroom and latin dancing. Apr 18 2024 11.00 - 12.00 Thursday, 18th April - 11am Guy Emerson : Seminar This event is co-organised by ILCC and by the UKRI Centre for Doctoral Training in Natural Language Processing, https://nlp-cdt.ac.uk. IF G.03 and Teams invite Contact
Thursday, 18th April - 11am Guy Emerson : Seminar Title: Truth conditions at scale, and beyond Abstract: Truth-conditional semantics has been successful in explaining how the meaning of a sentence can be decomposed into the meanings of its parts, and how this allows people to understand new sentences. In this talk, I will show how a truth-conditional model can be learnt in practice on large-scale datasets of various kinds (textual, visual, ontological), and how this provides empirical benefits compared to non-truth-conditional models. I will then take stock of the bigger picture, and argue it is (unfortunately) computationally intractable to reduce all kinds of language understanding to truth conditions. To enable a more complete account, I will sketch a new approach to approximate Bayesian modelling, with the potential to explain how patterns of language use arise as a result of resource-bounded minds interacting with a computationally demanding world. Bio: Guy Emerson is a computational semanticist at the University of Cambridge. He pursues research as an academic fellow at the Department of Computer Science & Technology, pursues teaching as a college lecturer at Gonville & Caius College, and promotes interdisciplinary work as an executive director of Cambridge Language Sciences. He also supports revitalisation of the Hokkien language, and enjoys ballroom and latin dancing. Apr 18 2024 11.00 - 12.00 Thursday, 18th April - 11am Guy Emerson : Seminar This event is co-organised by ILCC and by the UKRI Centre for Doctoral Training in Natural Language Processing, https://nlp-cdt.ac.uk. IF G.03 and Teams invite Contact
Apr 18 2024 11.00 - 12.00 Thursday, 18th April - 11am Guy Emerson : Seminar This event is co-organised by ILCC and by the UKRI Centre for Doctoral Training in Natural Language Processing, https://nlp-cdt.ac.uk.
