Paper

Capturing gradience in long-distance phonology using probabilistic tier-based strictly local grammars

Author
  • Connor Mayer (University of California, Los Angeles)

Abstract

Phonological processes often exhibit gradience, both in response frequencies and in acceptability judgments. This paper presents a variation of tier-based strictly local grammars, probabilistic tier-based strictly local (pTSL) grammars, which calculate the conditional probability that a given input string has some grammatical projection. pTSL grammars are well-suited to modeling gradience, particularly for long-distance processes, and naturally extend categorical tier-based strictly local grammars by probabilizing the projection function. After describing the formal properties of pTSL, I illustrate its application using data from Hungarian and Uyghur. pTSL is able to capture distance-based decay in these languages without an explicit notion of distance, and provides a unified account of gradient blocking and distance-based decay. I finish by outlining some of the limitations of pTSL, and how further extensions may overcome these.

Keywords: phonology, TSL, pTSL, long-distance, Uyghur, Hungarian, formal language theory, subregular phonology

How to Cite:

Mayer, C., (2021) “Capturing gradience in long-distance phonology using probabilistic tier-based strictly local grammars”, Society for Computation in Linguistics 4(1), 39-50. doi: https://doi.org/10.7275/231q-p480

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Published on
01 Jan 2021