Papers with multi-task training approaches

1 papers
Fortification of Neural Morphological Segmentation Models for Polysynthetic Minimal-Resource Languages (N18-1)

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Challenge: Morphological segmentation for polysynthetic languages is challenging because of limited training data.
Approach: They propose two new multi-task training approaches that improve performance for Mexican polysynthetic languages . they also propose cross-lingual transfer as a third way to fortify their neural model .
Outcome: The proposed models improve on Mexicanero, Nahuatl, Wixarika and Yorem Nokki . the proposed models reduce the amount of parameters by close to 75% .

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