Abstract
This paper presents a method for diacritics restoration based on learning mechanisms that act at letter level. This technique is new to our knowledge, and we compare it with the well known techniques for diacritics restoration that learn from words. Our method is particularly useful for languages that lack large electronic dictionaries and where means for generalization beyond words are required. Accuracies of over 99% at letter level are reported.
Cite
CITATION STYLE
Mihalcea, R. F. (2002). Diacritics restoration: Learning from letters versus learning from words. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2276, pp. 339–348). Springer Verlag. https://doi.org/10.1007/3-540-45715-1_35
Register to see more suggestions
Mendeley helps you to discover research relevant for your work.
