# A Survey of Resources and Methods for Natural Language Processing of Serbian Language

arXiv: https://arxiv.org/abs/2304.05468 · HTML: https://mlsanity.com/paper/2304.05468/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 14 of its 162 references that are in the map.
- First posted on arXiv 11 Apr 2023.

## Builds on (most cited first, 14 of 14)

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- [Enriching Word Vectors with Subword Information](https://mlsanity.com/paper/1607.04606/) (2016)
- [LaMDA: Language Models for Dialog Applications](https://mlsanity.com/paper/2201.08239/) (2022)
- [Cross-lingual Language Model Pretraining](https://mlsanity.com/paper/1901.07291/) (2019)
- [Multilingual Twitter Sentiment Classification: The Role of Human Annotators](https://mlsanity.com/paper/1602.07563/) (2016)
- [BERTi'c -- The Transformer Language Model for Bosnian, Croatian, Montenegrin and Serbian](https://mlsanity.com/paper/2104.09243/) (2021)
- [FinEst BERT and CroSloEngual BERT: less is more in multilingual models](https://mlsanity.com/paper/2006.07890/) (2020)
- [The ParlaSent-BCS dataset of sentiment-annotated parliamentary debates from Bosnia-Herzegovina, Croatia, and Serbia](https://mlsanity.com/paper/2206.00929/) (2022)
- [As Cool as a Cucumber: Towards a Corpus of Contemporary Similes in Serbian](https://mlsanity.com/paper/1605.06319/) (2016)
- [Creating a contemporary corpus of similes in Serbian by using natural language processing](https://mlsanity.com/paper/1811.10422/) (2018)

## Abstract (arXiv)

The Serbian language is a Slavic language spoken by over 12 million speakers and well understood by over 15 million people. In the area of natural language processing, it can be considered a low-resourced language. Also, Serbian is considered a high-inflectional language. The combination of many word inflections and low availability of language resources makes natural language processing of Serbian challenging. Nevertheless, over the past three decades, there have been a number of initiatives to develop resources and methods for natural language processing of Serbian, ranging from developing a corpus of free text from books and the internet, annotated corpora for classification and named entity recognition tasks to various methods and models performing these tasks. In this paper, we review the initiatives, resources, methods, and their availability.