International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Volume 8 Issue 3
May-June 2026

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Audio Forgery Detection System

Author(s) Mr. Adwait Ashish Sonawane, Mr. Kunal Kishor Turankar, Ms. Agasti Anil Chavan, Prof. Avinash Taskar
Country India
Abstract The rapid advancement of digital audio recording devices, mobile applications, and the Internet of Things (IoT) facilitates the collection and analysis of speech and audio data for applications such as voice authentication and smart embedded systems. However, the widespread availability of sophisticated audio editing tools, including Adobe Audition and various mobile apps, increases the risk of audio tampering for malicious purposes. This presents a critical challenge, especially in sensitive contexts such as legal proceedings, where manipulated audio may be presented as genuine evidence. Due to the cost and complexity of digital watermarking and signature-based techniques, most real-world audio recordings lack embedded authentication and remain vulnerable to forgery. Our implemented system focuses on developing an audio forgery detection system capable of identifying tampering in audio files, including copy-move and splicing forgeries. The system leverages linear-frequency cepstral coefficients (LFCCs) and machine learning techniques to detect manipulations with high accuracy and reliability. It outlines the functional requirements, system architecture, key methodologies, and the integration of deep learning models for tampering detection. The approach also addresses the challenges of detecting forgeries in realworld noisy environments and evaluates system performance using metrics such as accuracy, precision, and recall. Future directions include optimizing model inference and addressing emerging forgery techniques.
Keywords Audio forgery detection, copy-move forgery, audio splicing, machine learning, LFCC, real-time inference
Field Computer > Artificial Intelligence / Simulation / Virtual Reality
Published In Volume 8, Issue 3, May-June 2026
Published On 2026-05-05
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E-ISSN 2582-2160
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