At this week’s MCQLL meeting, Jacob Louis Hoover will be presenting When unpredictable doesn’t mean difficult.

Tuesday, November 21, 15:00–16:00 (Montréal time, UTC-5)
MCQLL meetings this semester are in hybrid format. We will meet in-person in room 117 of the McGill Linguistics Department, 1085 Dr-Penfield. If you’d like to attend virtually, the Zoom link is here.

All are welcome to attend.

  • Speaker:
    Jacob Louis Hoover
    When unpredictable doesn’t mean difficult

    When humans process linguistic input, we do so faster and with less effort when it better matches what we expect about the intended meaning. The relationship between a comprehender’s expectations about what is going to be said and their processing difficulty has been extensively studied in the computational psycholinguistics literature, documenting a robust correlation between a word’s difficulty (measured by behavioural psychometrics such as reading time) and its surprisal (defined as \(\log[1/\Pr(\text{word}\mid\text{context})]\), which can be estimated from statistics of language use). One important justification for this relationship is that, under certain simplifying assumptions, surprisal is equivalent of the comprehender’s Bayesian belief update \(\operatorname{D_{\mathrm{KL}}}(\text{posterior}\|\text{prior})\) about meanings, incurred upon observing the word. Less predictable words tend to incur larger updates.

    However, the equivalence between surprisal and belief update size doesn’t necessarily hold in general. In particular, processing of production errors (such as typos or spelling errors in written language) provide an intuitive source of counterexamples. I propose that such items, despite their being extremely unpredictable, often do not cause commensurately large processing effort.

    In this presentation I will be discussing a pilot study I am designing to explore these predictions, and welcome feedback on this preliminary work.

    I will be presenting remotely.