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A Joint Model of Orthography and Morphological Segmentation

Accepted version
Peer-reviewed

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Abstract

We present a model of morphological seg- mentation that jointly learns to segment and restore orthographic changes, e.g., funniest → fun-y-est. We term this form of analysis canon- ical segmentation and contrast it with the tra- ditional surface segmentation, which segments a surface form into a sequence of substrings, e.g., funniest → funn-i-est. We derive an im- portance sampling algorithm for approximate inference in the model and report experimental results on English, German and Indonesian.

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Journal Title

Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

Conference Name

Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies

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Volume Title

Publisher

Association for Computational Linguistics

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