Probabilistic Typology: Deep Generative Models of Vowel Inventories
May 04, 2017 ยท Declared Dead ยท ๐ Annual Meeting of the Association for Computational Linguistics
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Authors
Ryan Cotterell, Jason Eisner
arXiv ID
1705.01684
Category
cs.CL: Computation & Language
Citations
32
Venue
Annual Meeting of the Association for Computational Linguistics
Last Checked
6 months ago
Abstract
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.
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