Improving Deepfake Audio Detection: A Support Vector Machine Approach with Mel-Frequency Cepstral Coefficients

Authors

  • Shwetambari Borade Assistant Professor Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Nilakshi Jain Professor, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Bhavesh Patel Professor, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Vineet Kumar Founder & Global President, CyberPeace Foundation, Delhi, India
  • Mustansir Godhrawala Student, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Shubham Kolaskar Student, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Yash Nagare Student, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Pratham Shah Student, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India
  • Jayan Shah Student, Shah & Anchor Kutchhi Engineering College, Chembur, Mumbai, Maharashtra, India

Keywords:

Audio Analysis, Deepfake Detection, Feature Extraction, Media Manipulation, Mel-Frequency Cepstral Coefficients (MFCCs), Support Vector Machine (SVM)

Abstract

This paper presents a machine learning system designed to differentiate real from synthetic speech using a Support Vector Machine (SVM) classifier. Trained on the 'for-original' Fake-or-Real (FoR) dataset, which consists of over 195,000 genuine and computer-generated utterances, the system uses Mel Frequency Cepstral Coefficients (MFCCs) to extract features. Evaluation results show a promising accuracy of 97.28%, indicating the system's potential efficacy in real-world applications. The work lays the foundation for future improvements in detection robustness and reliability by highlighting the significance of raw data in classifier training for deepfake detection.

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References

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Published

24.03.2024

How to Cite

Borade, S. ., Jain, N. ., Patel, B. ., Kumar, V. ., Godhrawala, M. ., Kolaskar, S. ., Nagare, Y. ., Shah, P. ., & Shah, J. . (2024). Improving Deepfake Audio Detection: A Support Vector Machine Approach with Mel-Frequency Cepstral Coefficients. International Journal of Intelligent Systems and Applications in Engineering, 12(18s), 281–291. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4972

Issue

Vol. 12 No. 18s (2024)

Section

Research Article

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