Marathi-English Code-mixed Text Generation

Dhiraj Amin, Sharvari Govilkar, Sagar Kulkarni, Yash Shashikant Lalit, Arshi Ajaz Khwaja +2 more
9/28/2023
cs.CL

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Abstract

Code-mixing, the blending of linguistic elements from distinct languages to form meaningful sentences, is common in multilingual settings, yielding hybrid languages like Hinglish and Minglish. Marathi, India's third most spoken language, often integrates English for precision and formality. Developing code-mixed language systems, like Marathi-English (Minglish), faces resource constraints. This research introduces a Marathi-English code-mixed text generation algorithm, assessed with Code Mixing Index (CMI) and Degree of Code Mixing (DCM) metrics. Across 2987 code-mixed questions, it achieved an average CMI of 0.2 and an average DCM of 7.4, indicating effective and comprehensible code-mixed sentences. These results offer potential for enhanced NLP tools, bridging linguistic gaps in multilingual societies.

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Cite this paper

@article{amin2023marathienglish,
  title  = {Marathi-English Code-mixed Text Generation},
  author = {Dhiraj Amin and Sharvari Govilkar and Sagar Kulkarni and Yash Shashikant Lalit and Arshi Ajaz Khwaja and Daries Xavier and Sahil Girijashankar Gupta},
  year   = {2023},
  eprint = {2309.16202},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2309.16202v1}
}

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