Papers by Austin Matthews

1 papers
Using Morphological Knowledge in Open-Vocabulary Neural Language Models (N18-1)

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Challenge: Existing models that generate words from a fixed vocabulary are linguistically nave . authors present an open-vocabulary language model that incorporates morphological knowledge into a neural framework .
Approach: They propose a model that incorporates morphological knowledge into a neural model by generating words as a sequence of characters, generating full word forms and combining them with a hand-written morphology analyzer.
Outcome: The proposed model outperforms character-based models on Finnish, Turkish, and Russian on three languages.

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