Overview of Morpho challenge 2008
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Morpho challenge evaluation by information retrieval experiments
CLEF'08 Proceedings of the 9th Cross-language evaluation forum conference on Evaluating systems for multilingual and multimodal information access
Semi-supervised learning of concatenative morphology
SIGMORPHON '10 Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology
Morpho Challenge competition 2005--2010: evaluations and results
SIGMORPHON '10 Proceedings of the 11th Meeting of the ACL Special Interest Group on Computational Morphology and Phonology
Predicting reaction times in word recognition by unsupervised learning of morphology
ICANN'11 Proceedings of the 21th international conference on Artificial neural networks - Volume Part I
ACM Transactions on Speech and Language Processing (TSLP)
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In Morpho Challenge 2007, the objective was to design statistical machine learning algorithms that discover which morphemes (smallest individually meaningful units of language) words consist of. Ideally, these are basic vocabulary units suitable for different tasks, such as text understanding, machine translation, information retrieval, and statistical language modeling. Because in unsupervised morpheme analysis the morphemes can have arbitrary names, the analyses are here evaluated by a comparison to a linguistic gold standard by matching the morpheme-sharing word pairs. The data sets were provided for four languages: Finnish, German, English, and Turkish and the participants were encouraged to apply their algorithm to all of them. The results show significant variance between the methods and languages, but the best methods seem to be useful in all tested languages and match quite well with the linguistic analysis.