Romanian Diacritics Restoration Using Recurrent Neural Networks
Diacritics restoration is a mandatory step for adequately processing Romanian texts, and not a trivial one, as you generally need context in order to properly restore a character. Most previous methods which were experimented for Romanian restoration of diacritics do not use neural networks. Among those that do, there are no solutions specifically optimized for this particular language (i.e., they were generally designed to work on many different languages). Therefore we propose a novel neural architecture based on recurrent neural networks that can attend information at different levels of abstractions in order to restore diacritics.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Evaluating Large Language Models for Diacritic Restoration in Romanian Texts: A Comparative Study
Automatic diacritic restoration is crucial for text processing in languages with rich diacritical marks, such as Romanian. This study evaluates the performance of several large language models (LLMs) in restoring diacrit…
RoBERT -- A Romanian BERT Model
Deep pre-trained language models tend to become ubiquitous in the field of Natural Language Processing (NLP). These models learn contextualized representations by using a huge amount of unlabeled text data and obtain sta…
modelSentiment AnalysisTransfer LearningDiacritics Restoration using BERT with Analysis on Czech language
We propose a new architecture for diacritics restoration based on contextualized embeddings, namely BERT, and we evaluate it on 12 languages with diacritics. Furthermore, we conduct a detailed error analysis on Czech, a …
Croatian Text DiacritizationCzech Text DiacritizationFrench Text DiacritizationHungarian Text Diacritization+8Lexical Disambiguation of Igbo using Diacritic Restoration
Properly written texts in Igbo, a low-resource African language, are rich in both orthographic and tonal diacritics. Diacritics are essential in capturing the distinctions in pronunciation and meaning of words, as well a…
BIG-bench Machine LearningGeneral ClassificationDialectal and Low-Resource Machine Translation for Aromanian
This paper presents the process of building a neural machine translation system with support for English, Romanian, and Aromanian - an endangered Eastern Romance language. The primary contribution of this research is two…
Machine TranslationSentenceSentence EmbeddingSentence-Embedding+1