Muralidhar Palli


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2025

pdf bib
Team-Risers@DravidianLangTech 2025: AI-Generated Product Review Detection in Dravidian Languages Using Transformer-Based Embeddings
Sai Sathvik | Muralidhar Palli | Keerthana NNL | Balasubramanian Palani | Jobin Jose | Siranjeevi Rajamanickam
Proceedings of the Fifth Workshop on Speech, Vision, and Language Technologies for Dravidian Languages

Online product reviews influence customer choices and company reputations. However, companies can counter negative reviews by generating fake reviews that portray their products positively. These fake reviews lead to legal disputes and concerns, particularly because AI detection tools are limited in low-resource languages such as Tamil and Malayalam. To address this, we use machine learning and deep learning techniques to identify AI-generated reviews. We utilize Tamil BERT and Malayalam BERT in the embedding layer to extract contextual features. These features are sent to a Feedforward Neural Network (FFN) with softmax to classify reviews as AI-generated or not. The performance of the model is evaluated on the dataset. The results show that the transformer-based embedding achieves a better accuracy of 95.68\% on Tamil data and an accuracy of 88.75\% on Malayalam data.