# Survey on the Use of Typological Information in Natural Language Processing

arXiv: https://arxiv.org/abs/1610.03349 · HTML: https://mlsanity.com/paper/1610.03349/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 11 Oct 2016.

## Built on by (most cited first, 6 of 6)

- [Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer](https://mlsanity.com/paper/2105.05975/) (2021)
- [Does Typological Blinding Impede Cross-Lingual Sharing?](https://mlsanity.com/paper/2101.11888/) (2021)
- [Language Embeddings Sometimes Contain Typological Generalizations](https://mlsanity.com/paper/2301.08115/) (2023)
- [On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?](https://mlsanity.com/paper/2406.14267/) (2024)
- [Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?](https://mlsanity.com/paper/2110.07816/) (2021)
- [Kinship in Speech: Leveraging Linguistic Relatedness for Zero-Shot TTS in Indian Languages](https://mlsanity.com/paper/2506.03884/) (2025)

## Abstract (arXiv)

In recent years linguistic typology, which classifies the world's languages according to their functional and structural properties, has been widely used to support multilingual NLP. While the growing importance of typological information in supporting multilingual tasks has been recognised, no systematic survey of existing typological resources and their use in NLP has been published. This paper provides such a survey as well as discussion which we hope will both inform and inspire future work in the area.