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We train neural models for morphological analysis, generation andlemmatization for morphologically rich languages. We present a method forautomatically extracting substantially large amount of training data from FSTsfor 22 languages, out of which 17 are endangered. The neural models follow thesame tagset as the FSTs in order to make it possible to use them as fallbacksystems together with the FSTs. The source code, models and datasets have beenreleased on Zenodo.

Neural Morphology Dataset and Models for Multiple Languages, from the Large to the Endangered