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AI-Based Deepfake Voice Detection Model for Hindi LanguageBy Ashutosh Radheshyam Gaur, Atharva Santosh Dhumal, Ashwini Renavikar
Abstract: Most current research on deepfake voice detection focuses heavily on English or Mandarin, creating a significant security gap for Hindi speakers. To address this, we developed a detection framework specifically tailored for the Hindi language using a lightweight approach: Mel-Frequency Cepstral Coefficient (MFCC) feature extraction paired with an XGBoost classifier. We trained the system on a large dataset comprising over 99,000 real voice samples and roughly 3,800 synthetic samples, each …
Published in International Journal of Image Processing and Pattern Recognition · Vol. 12, Issue 2, 2026 Read article →