18 January 2019 - Ryan Cotterell: Seminar
Probabilistic Typology: Deep Generative Models of Vowel Inventories
Linguistic typology studies the range of structures present in human language. The main goal of the field is to discover which sets of possible phenomena are universal, and which are merely frequent. For example, all languages have vowels, while most—but not all—languages have an [u] sound. In this paper we present the first probabilistic treatment of a basic question in phonological typology: What makes a natural vowel inventory? We introduce a series of deep stochastic point processes, and contrast them with previous computational, simulation-based approaches. We provide a comprehensive suite of experiments on over 200 distinct languages.
Ryan is a lecturer (≈assistant professor) of computer science at the University of Cambridge. He specializes in natural language processing, computational linguistics and machine learning, focusing on deep learning and statistical approaches to phonology, morphology, linguistic typology and low-resource languages. He will receive his Ph.D. in Spring 2019 from the computer science department of the Johns Hopkins University, where he was affiliated with the Center for Language and Speech Processing; he was co-advised there by Jason Eisner and David Yarowsky. He has received best paper awards at ACL 2017 and EACL 2017 and two honorable mentions for best paper at EMNLP 2015 and NAACL 2016. Previously, he was a visiting Ph.D. student at the Center for Information and Language Processing at LMU Munich supported by a Fulbright Fellowship and a DAAD Research Grant under the supervision of Hinrich Schütze. His PhD was supported by an NDSEG graduate fellowship, the Fredrick Jelinek Fellowship, and a Facebook Fellowship.