IruMozhi: Automatically classifying diglossia in Tamil
Not on the map. Why?
Abstract (arXiv)
Tamil, a Dravidian language of South Asia, is a highly diglossic language with two very different registers in everyday use: Literary Tamil (preferred in writing and formal communication) and Spoken Tamil (confined to speech and informal media). Spoken Tamil is under-supported in modern NLP systems. In this paper, we release IruMozhi, a human-annotated dataset of parallel text in Literary and Spoken Tamil. We train classifiers on the task of identifying which variety a text belongs to. We use these models to gauge the availability of pretraining data in Spoken Tamil, to audit the composition of existing labelled datasets for Tamil, and to encourage future work on the variety.
Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 9 of its 27 references that are in the map. First posted on arXiv 13 Nov 2023.
Builds on
9 of 27 references.
References · 9
- 2019Unsupervised Cross-lingual Representation Learning at Scalecited by 3,907
- 2018UMAP: Uniform Manifold Approximation and Projection for Dimension Reductioncited by 2,841
- 2018A Call for Clarity in Reporting BLEU Scorescited by 1,790
- 2020The State and Fate of Linguistic Diversity and Inclusion in the NLP Worldcited by 789
- 2020Corpus Creation for Sentiment Analysis in Code-Mixed Tamil-English Textcited by 67
- 2020Processing South Asian Languages Written in the Latin Script: the Dakshina Datasetcited by 35
- 2021Few-shot Controllable Style Transfer for Low-Resource Multilingual Settingscited by 20
- 2018A Dataset for Building Code-Mixed Goal Oriented Conversation Systemscited by 16
- 2022Computational historical linguistics and language diversity in South Asiacited by 8
Built on by
Citing papers per year: 2025: 1.
1 paper.