A Comparative Study of Word Processors for Automatic Spell and Grammar Correction in Indian Languages

Abstract

The increasing use of digital content in Indian languages has created a growing demand for reliable word processors capable of providing accurate spell and grammar correction. Although several commercial and open-source word processors offer multilingual writing assistance, their effectiveness across Indian languages varies significantly due to differences in linguistic resources, Natural Language Processing (NLP) techniques, and Artificial Intelligence (AI) based correction mechanisms. This study presents a comparative evaluation of seven widely used word processors Microsoft Word, Google Docs, LibreOffice Writer, Zoho Writer, Indic WP, WPS Writer, and Notepad++ with respect to their support for Indian languages, spell checking, grammar correction, multilingual compatibility, and underlying technologies.
The comparison was conducted using a structured evaluation framework based on language coverage, spell-check availability, grammar-check support, correction mechanisms, platform type, and usability. The collected information was analyzed through comparative tables and graphical visualization to identify the strengths and limitations of each platform for multilingual writing. The findings indicate that cloud-based platforms, particularly Google Docs and Zoho Writer, provide context-aware AI-assisted writing support, whereas Microsoft Word demonstrates strong multilingual spell-checking capabilities through NLP-based techniques. LibreOffice offers effective offline spell-checking using the Hunspell engine, while Indic WP focuses on phonetic typing and Indic script support. However, reliable grammar correction remains limited for several Indian languages, especially Gujarati and other regional languages.
The study highlights the need for advanced transformer-based multilingual language models and larger annotated datasets to improve automatic spell and grammar correction for Indian languages. The findings may assist researchers, software developers, and multilingual users in selecting appropriate word processors and identifying future research directions for Indian language writing assistance.