The EMILE 4.1 Grammar Induction Toolbox
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Implementing Alignment-Based Learning
ICGI '02 Proceedings of the 6th International Colloquium on Grammatical Inference: Algorithms and Applications
Inducing Probabilistic Grammars by Bayesian Model Merging
ICGI '94 Proceedings of the Second International Colloquium on Grammatical Inference and Applications
Data-Oriented Parsing
Introduction to the special issue on computational linguistics using large corpora
Computational Linguistics - Special issue on using large corpora: I
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 2
A generative constituent-context model for improved grammar induction
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Early lexical development in a self-organizing neural network
Neural Networks - 2004 Special issue: New developments in self-organizing systems
Corpus-based induction of syntactic structure: models of dependency and constituency
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Annealing techniques for unsupervised statistical language learning
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
An all-subtrees approach to unsupervised parsing
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Part of speech tagging in context
COLING '04 Proceedings of the 20th international conference on Computational Linguistics
Problems with Evaluation of Unsupervised Empirical Grammatical Inference Systems
ICGI '08 Proceedings of the 9th international colloquium on Grammatical Inference: Algorithms and Applications
Unsupervised parsing with U-DOP
CoNLL-X '06 Proceedings of the Tenth Conference on Computational Natural Language Learning
High-accuracy annotation and parsing of CHILDES transcripts
CACLA '07 Proceedings of the Workshop on Cognitive Aspects of Computational Language Acquisition
Verifying Theories of Language Acquisition Using Computer Models of Language Evolution
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Natural language grammar induction with a generative constituent-context model
Pattern Recognition
Automatic evaluation of syntactic learners in typologically-different languages
Cognitive Systems Research
Searching the annotated Portuguese childes corpora
Proceedings of the Workshop on Computational Models of Language Acquisition and Loss
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Child language acquisition, one of Nature's most fascinating phenomena, is to a large extent still a puzzle. Experimental evidence seems to support the view that early language is highly formulaic, consisting for the most part of frozen items with limited productivity. Fairly quickly, however, children find patterns in the ambient language and generalize them to larger structures, in a process that is not yet well understood. Computational models of language acquisition can shed interesting light on this process. This paper surveys various works that address language learning from data; such works are conducted in different fields, including psycholinguistics, cognitive science and computer science, and we maintain that knowledge from all these domains must be consolidated in order for a well-informed model to emerge. We identify the commonalities and differences between the various existing approaches to language learning, and specify desiderata for future research that must be considered by any plausible solution to this puzzle.