HinglishCap: A Code Mixed Hindi-English Image Captioning Framework

Santosh Kumar Mishra

doi:10.1007/978-981-96-7008-6_26

HinglishCap: A Code Mixed Hindi-English Image Captioning Framework

2026-01-01

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Santosh Kumar Mishra *

Pushpak Bhattacharyya

DOI：10.1007/978-981-96-7008-6_26

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Multilingual speakers all over the globe often switch between languages known as code-mixing during communication or the employment of two or more languages in a single statement. Most of the works on code-mixing have been accomplished on text classification, question answering, dialogue understanding, etc. However, no specific research has been carried out on code-mixed image captioning in the past. We present an English-Hindi code-mixed image captioning dataset. We experiment with a novel architecture utilizing Faster-R CNN and Transformer as encoder and decoder with a geometric attention mechanism and other baselines. The code mixed dataset is created from a manually annotated parallel corpus of the MS COCO dataset in English and Hindi. Experimental findings show that the proposed technique surpasses the baselines in codemixed situations.

Keywords:

Code Mixing

Hindi

Image Captioning

Deep Learning

HinglishCap: A Code Mixed Hindi-English Image Captioning Framework

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