Marathi-English Code-mixed Text Generation
This addresses resource constraints for developing NLP tools in multilingual societies like India, though it appears incremental as it applies existing metrics to a new language pair.
The research tackled the problem of generating Marathi-English code-mixed text, achieving an average Code Mixing Index of 0.2 and Degree of Code Mixing of 7.4 across 2987 questions, indicating effective and comprehensible sentences.
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.