Papers with automatic morphological inflection generation

1 papers
Pushing the Limits of Low-Resource Morphological Inflection (D19-1)

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Challenge: Recent advances in morphological inflection generation have limited resources . antonisa and colleagues present a battery of improvements to improve performance under low-resource conditions .
Approach: They propose a two-step attention architecture for the inflection decoder that uses two-segments attention and a multi-single-syllabic attention architecture.
Outcome: The proposed model outperforms the state-of-the-art in low-resource languages by 15 percentage points . the proposed model also shows that it can be used to model monolingual data hallucinations .

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