Tags:distributional semantics, model theory and speaker alignment
Abstract:
One long-standing puzzle in semantics is the ability of speakers to refer successfully in spite of holding different models of the world. This puzzle is famously illustrated by the cup/mug example: if two speakers disagree on whether a specific entity is a cup or a mug (i.e. if their interpretation functions differ), how can they align so that the entity can still be talked about?
Another puzzle, coming to us through lexical and distributional semantics, is that word meaning seems to be infinitely flexible, indeed much more so than the traditional notion of sense would have it. This makes the alignment process between speakers even more unpredictable.
In this talk, I will report on a series of experiments aiming at investigating what differences in language use can tell us about the ability of speakers to align at a model-theoretic level. Since speaker-dependent data is extremely hard to obtain, I propose a new methodology to 'spawn' speakers from a reference distributional semantic space, corresponding to different types of variations in language use. I show how and where alignment is disturbed, and give a theoretical account of how such perturbations relate to potentially catastrophic differences in world representations.
Speakers in vats: simulating model-theoretic alignment with distributional semantics