Papers by Ajay Mishra

2 papers
A Multitask Learning Approach for Diacritic Restoration (2020.acl-main)

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Challenge: Diacritics are used to specify pronunciations and meanings in many languages like Arabic.
Approach: They propose to use multi-task learning to optimize diacritic restoration with related NLP problems . they use Arabic as a case study since it has sufficient data resources for tasks .
Outcome: The proposed model outperforms baseline models and is comparable to the state-of-the-art models.
Efficient Convolutional Neural Networks for Diacritic Restoration (D19-1)

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Challenge: Diacritic restoration is a computational task that requires a computer to understand written texts.
Approach: They propose to use Temporal Convolutional Neural Networks (TCN) to restore missing diacritics for each character in written text.
Outcome: The proposed model improves on TCN in Arabic, Yoruba, and Vietnamese.

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