Marathi-English Code-mixed Text Generation

TL;DR

This paper presents a novel Marathi-English code-mixed text generation method that effectively produces comprehensible hybrid sentences, aiding multilingual NLP applications despite resource limitations.

Contribution

It introduces a new algorithm for Marathi-English code-mixed text generation and evaluates it using standard code-mixing metrics on a substantial dataset.

Findings

Achieved an average CMI of 0.2 indicating moderate code mixing.

Achieved an average DCM of 7.4 showing effective code blending.

Demonstrated potential for improved multilingual NLP tools.

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.