… seeks to understand the remarkable efficiency of language comprehension, using the tools of probability theory and statistical decision theory as explanatory frameworks. My work suggests that we achieve communicative efficiency by utilizing rich, structured probabilistic information about language: leveraging linguistic redundancy to fill in details absent from the perceptual signal, to spend less time processing more frequent material, and to make predictions about language material not yet encountered.
Klinton is a UCSD graduate, where he worked with Roger Levy, Keith Rayner, Jeff Elman, Martha Kutas, among others. He spent the first two years of his post-doc life at UCSD, before he joined Rochester as an NIH-funded post-doctoral fellow at the Center of Language Sciences. As an example of some of his recent work at Rochester, here’s his CUNY 2014 poster on the extent to which information about the speech signal is still available during lexical processing and the extent to which the resulting uncertainty about the signal is maintained over time even after the word has been observed (cf. right context effects; paper to come soon):