Image Processing-Based Transliteration from Hindi to English

doi:10.23940/ijpe.23.05.p5.334341

Abstract

Abstract: A word or text is transliterated when it is changed from one script to another while retaining its phonetic and orthographic characteristics. Natural language processing includes transliteration, which is crucial for connecting with speakers of other languages. Since Hindi is the official language of India and there is a vast amount of content in Hindi that needs to be transliterated into English for usage on a regional and foreign scale, this paper focuses on that method. Hindi must be transliterated into English in order for speakers of other languages to understand and interact with Hindi. The present study describes a hybrid method for Hindi to English transliteration that incorporates image processing and an attention-trained model, as well as its applications in many domains. The system's performance is assessed using a dataset of images of Hindi text, and the results demonstrate that the suggested method outperforms previous transliteration systems in terms of both accuracy and speed.

Key words: transliteration, image processing, machine learning, natural language processing

Mahima Yadav and Ishan Kumar. Image Processing-Based Transliteration from Hindi to English [J]. Int J Performability Eng, 2023, 19(5): 334-341.

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