On learning the past tenses of English verbs
Parallel distributed processing: explorations in the microstructure of cognition, vol. 2
Regular models of phonological rule systems
Computational Linguistics - Special issue on computational phonology
Learning bias and phonological-rule induction
Computational Linguistics
Machine Learning - Special issue on inducive logic programming
Learning the past tense of English verbs using inductive logic programming
Connectionist, Statistical, and Symbolic Approaches to Learning for Natural Language Processing
Learning Multilingual Morphology with CLOG
ILP '98 Proceedings of the 8th International Workshop on Inductive Logic Programming
Sparse Representations for Fast, One-Shot Learning
Sparse Representations for Fast, One-Shot Learning
Modeling and learning multilingual inflectional morphology in a minimally supervised framework
Modeling and learning multilingual inflectional morphology in a minimally supervised framework
Unsupervised learning of the morphology of a natural language
Computational Linguistics
Bootstrapping morphological analyzers by combining human elicitation and machine learning
Computational Linguistics
Automatic acquisition of two-level morphological rules
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
A discovery procedure for certain phonological rules
ACL '84 Proceedings of the 10th International Conference on Computational Linguistics and 22nd annual meeting on Association for Computational Linguistics
Part-of-speech induction from scratch
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Machine learning of morphological rules by generalization and analogy
COLING '86 Proceedings of the 11th coference on Computational linguistics
Unsupervised discovery of phonological categories through supervised learning of morphological rules
COLING '96 Proceedings of the 16th conference on Computational linguistics - Volume 1
Proceedings of the ninth ACM SIGPLAN international conference on Functional programming
A probabilistic model for stemmer generation
Information Processing and Management: an International Journal - Special issue: An Asian digital libraries perspective
Combining distributional and morphological information for part of speech induction
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
A Bayesian model for morpheme and paradigm identification
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Memory-Based Learning of morphology with stochastic transducers
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Knowledge-free induction of inflectional morphologies
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Unsupervised segmentation of words using prior distributions of morph length and frequency
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Minimally supervised morphological analysis by multimodal alignment
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Knowledge-free induction of morphology using latent semantic analysis
ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
Unsupervised learning of morphology using a novel directed search algorithm: taking the first step
MPL '02 Proceedings of the ACL-02 workshop on Morphological and phonological learning - Volume 6
An algorithm for the unsupervised learning of morphology
Natural Language Engineering
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Toward unsupervised whole-corpus tagging
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Efficient unsupervised recursive word segmentation using minimum description length
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Morpholog: Constrained and Supervised Learning of Morphology
ConLL '01 Proceedings of the 2001 workshop on Computational Natural Language Learning - Volume 7
Unsupervised part-of-speech tagging employing efficient graph clustering
COLING ACL '06 Proceedings of the 21st International Conference on computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics: Student Research Workshop
Structures and distributions in morphology learning
Structures and distributions in morphology learning
The proper treatment of optimality in computational phonology: plenary talk
FSMNLP '09 Proceedings of the International Workshop on Finite State Methods in Natural Language Processing
Unsupervised learning of Bulgarian POS tags
MorphSlav '03 Proceedings of the 2003 EACL Workshop on Morphological Processing of Slavic Languages
Latent-variable modeling of string transductions with finite-state methods
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Learning the past tense of English verbs: the symbolic pattern associator vs. connectionist models
Journal of Artificial Intelligence Research
Unsupervised morphological segmentation with log-linear models
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Induction of a simple morphology for highly-inflecting languages
SIGMorPhon '04 Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology
Multilingual noise-robust supervised morphological analysis using the WordFrame model
SIGMorPhon '04 Proceedings of the 7th Meeting of the ACL Special Interest Group in Computational Phonology: Current Themes in Computational Phonology and Morphology
Using morphology and syntax together in unsupervised learning
PMHLA '05 Proceedings of the Workshop on Psychocomputational Models of Human Language Acquisition
The SED heuristic for morpheme discovery: a look at Swahili
PMHLA '05 Proceedings of the Workshop on Psychocomputational Models of Human Language Acquisition
Improving morphology induction by learning spelling rules
IJCAI'09 Proceedings of the 21st international jont conference on Artifical intelligence
An analogical learner for morphological analysis
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Morphology induction from term clusters
CONLL '05 Proceedings of the Ninth Conference on Computational Natural Language Learning
Computing with realizational morphology
CICLing'03 Proceedings of the 4th international conference on Computational linguistics and intelligent text processing
Overview and results of Morpho challenge 2009
CLEF'09 Proceedings of the 10th cross-language evaluation forum conference on Multilingual information access evaluation: text retrieval experiments
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We develop an unsupervised algorithm for morphological acquisition to investigate the relationship between linguistic representation, data statistics, and learning algorithms. We model the phenomenon that children acquire the morphological inflections of a language monotonically by introducing an algorithm that uses a bootstrapped, frequency-driven learning procedure to acquire rules monotonically. The algorithm learns a morphological grammar in terms of a Base and Transforms representation, a simple rule-based model of morphology. When tested on corpora of child-directed speech in English from CHILDES (MacWhinney in The CHILDES-Project: Tools for analyzing talk. Erlbaum, Hillsdale, 2000), the algorithm learns the most salient rules of English morphology and the order of acquisition is similar to that of children as observed by Brown (A first language: the early stages. Harvard University Press, Cambridge, 1973). Investigations of statistical distributions in corpora reveal that the algorithm is able to acquire morphological grammars due to its exploitation of Zipfian distributions in morphology through type-frequency statistics. These investigations suggest that the computation and frequency-driven selection of discrete morphological rules may be important factors in children's acquisition of basic inflectional morphological systems.