Abstract
During early language acquisition, infants must learn both a lexicon and a model of phonetics that explains how lexical items can vary in pronunciation– for instance “you” might be realized as ‘you’ with a full vowel or reduced to ‘yeh’ with a schwa. Previous models of acquisition have generally tackled these problems in isolation, yet behavioral evidence suggests infants acquire lexical and phonetic knowledge simultaneously. I will present ongoing research on constructing a Bayesian model which can simultaneously group together phonetic variants of the same lexical item, learn a probabilistic language model predicting the next word in an utterance from its context, and learn a model of pronunciation variability based on articulatory features.I will discuss a model which takes word boundaries as given and focuses on clustering the lexical items (published at ACL 2012). I will also give preliminary results for a model which searches for word boundaries at the same time as performing the clustering.
Biography
Micha Elsner is an Assistant Professor of Linguistics at the Ohio State University, where he started in August. He completed his PhD in 2011 at Brown University, working on models of local coherence. He then worked on Bayesian models of language acquisition as a postdoctoral researcher at the University of Edinburgh.