Papers with diacritics restoration

3 papers
Diacritics Restoration Using Neural Networks (L18-1)

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Challenge: a novel combination of character-level recurrent neural network and language model is proposed . people often replace characters with diacritics with their ASCII counterparts .
Approach: They propose a character-level recurrent neural network-based model and a language model for diacritics restoration.
Outcome: The proposed model reduces error of current best systems by 20% to 64% on four languages . it is also able to restore diacritical marks on a number of languages using the same model .
Dilated Convolutional Neural Networks for Lightweight Diacritics Restoration (2022.lrec-1)

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Challenge: Diacritics restoration is a ubiquitous task in the Latin-alphabet-based English-dominated Internet language environment.
Approach: They propose a 1D dilated convolution-based approach which operates on a character-level.
Outcome: The proposed approach surpasses similar models and is competitive with larger models.
RoBERT – A Romanian BERT Model (2020.coling-main)

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Challenge: Existing pre-trained language models learn contextualized representations by using unlabeled text data and obtain state of the art results on a multitude of NLP tasks.
Approach: They propose a pre-trained BERT model for Romanian language processing and compare it with multi-lingual models on seven Romanian specific NLP tasks.
Outcome: The proposed model outperforms multi-lingual models on seven Romanian specific NLP tasks on sentiment analysis, dialect and cross-dialect topic identification, and diacritics restoration.

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