Learning Interactions of Local and Non-Local Phonotactic Constraints from Positive Input
- Aniello De Santo (University of Utah)
- Alëna Aksënova (Google NYC)
Abstract
This paper proposes a grammatical inference algorithm to learn input-sensitive tier-based strictly local languages across multiple tiers from positive data only, when the locality of the tier-constraints and the tier-projection function is set to 2 (MITSL; De Santo and Graf, 2019). We conduct simulations showing that the algorithm succeeds in learning MITSL patterns over a set of artificial languages.
Keywords: Grammatical inference, subregular languages, learning, phonotactics, formal language theory
How to Cite:
De Santo, A. & Aksënova, A., (2021) “Learning Interactions of Local and Non-Local Phonotactic Constraints from Positive Input”, Society for Computation in Linguistics 4(1), 167-176. doi: https://doi.org/10.7275/m1ab-qv64
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