A Comparative Survey of Text Summarization For Indian Languages

In Natural Language Processing (NLP), text summarization is an essential activity that aims to reduce massive text volumes into shorter, coherent versions while maintaining important information. While summarizing technologies have advanced greatly for major languages such as English, the development and implementation of summarization for Indian languages is still in its infancy. This research includes a comprehensive comparative review of text summarization methodologies in six major Indian languages, as well as a uniform evaluation framework. By methodically examining both extractive and abstractive summarizing techniques, we pinpoint important research voids and offer cross-linguistic perspectives that can direct further investigation. Through this analysis, we uncover previously unidentified relationships between language characteristics and summarization approach effectiveness, giving a structured roadmap for future improvements in Indian language text summarization.