  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.
