# Normalization of Lithuanian Text Using Regular Expressions

arXiv: https://arxiv.org/abs/2312.17660 · HTML: https://mlsanity.com/paper/2312.17660/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 32 references that are in the map.
- First posted on arXiv 29 Dec 2023.

## Builds on (most cited first, 2 of 2)

- [RNN Approaches to Text Normalization: A Challenge](https://mlsanity.com/paper/1611.00068/) (2016)
- [An improved Bayesian TRIE based model for SMS text normalization](https://mlsanity.com/paper/2008.01297/) (2020)

## Abstract (arXiv)

Text Normalization is an integral part of any text-to-speech synthesis system. In a natural language text, there are elements such as numbers, dates, abbreviations, etc. that belong to other semiotic classes. They are called non-standard words (NSW) and need to be expanded into ordinary words. For this purpose, it is necessary to identify the semiotic class of each NSW. The taxonomy of semiotic classes adapted to the Lithuanian language is presented in the work. Sets of rules are created for detecting and expanding NSWs based on regular expressions. Experiments with three completely different data sets were performed and the accuracy was assessed. Causes of errors are explained and recommendations are given for the development of text normalization rules.