mlsanityData to 7 Oct 2026

IndiText Boost: Text Augmentation for Low Resource India Languages

arXiv 2401.13085 ↗First posted 23 Jan 2024cs.CL cs.AI cs.LGcited by 4

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Abstract (arXiv)

Text Augmentation is an important task for low-resource languages. It helps deal with the problem of data scarcity. A data augmentation strategy is used to deal with the problem of data scarcity. Through the years, much work has been done on data augmentation for the English language. In contrast, very less work has been done on Indian languages. This is contrary to the fact that data augmentation is used to deal with data scarcity. In this work, we focus on implementing techniques like Easy Data Augmentation, Back Translation, Paraphrasing, Text Generation using LLMs, and Text Expansion using LLMs for text classification on different languages. We focus on 6 Indian languages namely: Sindhi, Marathi, Hindi, Gujarati, Telugu, and Sanskrit. According to our knowledge, no such work exists for text augmentation on Indian languages. We carry out binary as well as multi-class text classification to make our results more comparable. We get surprising results as basic data augmentation techniques surpass LLMs.

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 13 of its 25 references that are in the map. First posted on arXiv 23 Jan 2024.

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13 of 25 references.

References · 13

  1. 2019EDA: Easy Data Augmentation Techniques for Boosting Performance on Text Classification Taskscited by 800
  2. 2015Improving Neural Machine Translation Models with Monolingual Datacited by 784
  3. 2021A Survey of Data Augmentation Approaches for NLPcited by 408
  4. 2018Contextual Augmentation: Data Augmentation by Words with Paradigmatic Relationscited by 201
  5. 2020MixText: Linguistically-Informed Interpolation of Hidden Space for Semi-Supervised Text Classificationcited by 186
  6. 2019Good-Enough Compositional Data Augmentationcited by 158
  7. 2017Data Augmentation for Low-Resource Neural Machine Translationcited by 139
  8. 2020Syntactic Data Augmentation Increases Robustness to Inference Heuristicscited by 85
  9. 2018SwitchOut: an Efficient Data Augmentation Algorithm for Neural Machine Translationcited by 72
  10. 2020Sequence-Level Mixed Sample Data Augmentationcited by 71
  11. 2019Data Augmentation via Dependency Tree Morphing for Low-Resource Languagescited by 45
  12. 2020Hostility Detection Dataset in Hindicited by 31
1 more
  1. 2020iNLTK: Natural Language Toolkit for Indic Languagescited by 24

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Citing papers per year: 2024: 1; 2025: 3.

4 papers.

  1. 2025Bhaasha, Bhasa, Zaban: A Survey for Low-Resourced Languages in South Asia -- Current Stage and Challengescited by 6
  2. 2024Decoding the Diversity: A Review of the Indic AI Research Landscapecited by 4
  3. 2025Enhancing NER Performance in Low-Resource Pakistani Languages using Cross-Lingual Data Augmentationcited by 2
  4. 2025MAGE: Multi-Head Attention Guided Embeddings for Low Resource Sentiment Classificationcited by 1