The benefits of errors: learning an OT grammar with a structured candidate set

Authors:
Tamás Biró
Affiliations:
Universiteit van Amsterdam, Amsterdam, The Netherlands
Venue:
CACLA '07 Proceedings of the Workshop on Cognitive Aspects of Computational Language Acquisition
Year:
2007

Citing 4
Cited 0

Computational optimality theory

Computational optimality theory
Efficient generation in primitive Optimality Theory

ACL '98 Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and Eighth Conference of the European Chapter of the Association for Computational Linguistics
Processing optimality-theoretic syntax by interleaved chart parsing and generation

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
The Harmonic Mind: From Neural Computation to Optimality-Theoretic GrammarVolume I: Cognitive Architecture (Bradford Books)

The Harmonic Mind: From Neural Computation to Optimality-Theoretic GrammarVolume I: Cognitive Architecture (Bradford Books)

Quantified Score

Hi-index	0.00

Visualization

Abstract

We compare three recent proposals adding a topology to OT: McCarthy's Persistent OT, Smolensky's ICS and Bíró's SA-OT. To test their learnability, constraint rankings are learnt from SA-OT's output. The errors in the output, being more than mere noise, follow from the topology. Thus, the learner has to reconstructs her competence having access only to the teacher's performance.