Deepfake Audio Detection Leveraging Machine Learning and Deep Learning Models
International Research Journal of Modernization in Engineering Technology and Science · 2025
The advent of deep-fake technology poses unprecedented challenges in safeguarding the authenticity of audio content, necessitating the development of robust detection mechanisms.The rapid advancement in artificial intelligence has led to the emergence of deepfake audio, a technique where synthetic voices are generated to closely mimic real human speech.This study presents a comprehensive investigation into deep-fake audio detection using machine learning.Drawing from con temporary advancements in the field, the research explores a range of methodologies including Convolutional Neural Networks (CNN), Generative Adversial Networks (MFCC).The proposed approach encompasses the fusion of multiple deep learning models through ensemble learning to enhance overall detection accuracy.The study provides critical insights into the efficacy of machine learning methods in addressing the proliferation of deep-fake audio and aims to advance the development of reliable detection systems.