Survey on the Use of Typological Information in Natural Language Processing
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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.
Key facts. Cited by 6 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Oct 2016.
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Citing papers per year: 2021: 3; 2022: 0; 2023: 1; 2024: 1; 2025: 1.
6 papers.
- 2021Analysing The Impact Of Linguistic Features On Cross-Lingual Transfercited by 16
- 2021Does Typological Blinding Impede Cross-Lingual Sharing?cited by 9
- 2023Language Embeddings Sometimes Contain Typological Generalizationscited by 9
- 2024On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?cited by 5
- 2021Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?cited by 2
- 2025Kinship in Speech: Leveraging Linguistic Relatedness for Zero-Shot TTS in Indian Languagescited by 0
- 2025Kinship in Speech: Leveraging Linguistic Relatedness for Zero-Shot TTS in Indian Languages4 Jun 2025
- 2024On the Evaluation Practices in Multilingual NLP: Can Machine Translation Offer an Alternative to Human Translations?20 Jun 2024
- 2023Language Embeddings Sometimes Contain Typological Generalizations19 Jan 2023
- 2021Multilingual Neural Machine Translation:Can Linguistic Hierarchies Help?15 Oct 2021
- 2021Analysing The Impact Of Linguistic Features On Cross-Lingual Transfer12 May 2021
- 2021Does Typological Blinding Impede Cross-Lingual Sharing?28 Jan 2021