Communications of the ACM - Special issue on parallelism
On learning the past tenses of english verbs
Parallel distributed processing
Instance-Based Learning Algorithms
Machine Learning
Inside Case-Based Reasoning
Machine Learning
Learning bias and phonological-rule induction
Computational Linguistics
The Journal of Machine Learning Research
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Decision-tree based error correction for statistical phrase break prediction in Korean
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
Memory-based morphological analysis
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Modularity in inductively-learned word pronunciation systems
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
Do not forget: full memory in memory-based learning of word pronunciation
NeMLaP3/CoNLL '98 Proceedings of the Joint Conferences on New Methods in Language Processing and Computational Natural Language Learning
Instance-based acquisition of vowel harmony
SIGMORPHON '10 Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology
Case retrieval nets for heuristic lexicalization in natural language generation
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Case-based reasoning for knowledge-intensive template selection during text generation
ECCBR'06 Proceedings of the 8th European conference on Advances in Case-Based Reasoning
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A data-oriented (empiricist) alternative to the currently pervasive (nativist) Principles and Parameters approach to the acquisition of stress assignment is investigated. A similarity-based algorithm, viz. an augmented version of Instance-Based Learning is used to learn the system of main stress assignment in Dutch. In this nontrivial task a comprehensive lexicon of Dutch monomorphemes is used instead of the idealized and highly simplified description of the empirical data used in previous approaches.It is demonstrated that a similarity-based learning method is effective in learning the complex stress system of Dutch. The task is accomplished without the a priori knowledge assumed to pre-exist in the learner in a Principles and Parameters framework.A comparison of the system's behavior with a consensus linguistic analysis (in the framework of Metrical Phonology) shows that ease of learning correlates with decreasing degrees of markedness of metrcal phenomena. It is also shown that the learning algorithm captures subregularities within the stress system of Dutch that cannot be described without going beyond some of the theoretical assumptions of metrical phonology.