Paper

Learning Process Interaction Through Simplex ISL Transducers

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Abstract

This paper investigates the learnability of interacting phonological processes by restricting the hypothesis space to a subregular class of functions. Interacting processes can be modeled as function composition, where the output of one function serves as the input to another. We focus specifically on interactions between two simplex Input Strictly Local (ISL₂) functions, a proper subclass of the ISL function class. We propose a decomposition algorithm that reconstructs both the individual component processes and their relative ordering by exploiting structural properties of simplex ISL₂ transducers and their compositions. This work provides an initial step toward understanding how learners can infer not only single phonological processes, but also structured interactions between processes.

How to Cite:

Wang, C. & Jardine, A., (2026) “Learning Process Interaction Through Simplex ISL Transducers”, Society for Computation in Linguistics 9(1). doi: https://doi.org/10.7275/scil.4053