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  • media-sec-lab Audio-Deepfake-Detection - GitHub
    Resources on Audio Large Language Models, including datasets, methods, benchmarks, and studies A list of tools, papers and code related to Fake Audio Detection Sub-repositories include ASVspoof 5, ASVspoof 2021, and classifier-adjacency ⬆ Back to top 1
  • Unmasking Deepfakes: Leveraging Augmentations and Features Variability . . .
    In this paper, we propose a hybrid architecture for deepfake speech detection, combining a self-supervised learning framework for feature extraction with a classifier head to form an end-to-end model Our approach incorporates both audio-level and feature-level augmentation techniques
  • Deepfake Audio Detection Using MFCC Features - ijfmr. com
    By analyzing subtle inconsistencies in the audio signals, the system can accurately identify deepfake content, thereby enhancing the integrity of digital communications
  • Deepfake Detection – Protecting Identity Systems from AI-Generated . . .
    Understanding Deepfake Technology and Its Risks Deepfakes rely on advanced machine learning architectures: Generative Adversarial Networks (GANs): Two neural networks (generator and discriminator) compete to create realistic synthetic media
  • A survey on multimedia-enabled deepfake detection: state-of-the-art . . .
    Spoofing in Audio: Assessing and identifying speech synthesis and artificial voices in cloned audio is known as "spoofing" in audio Multimodal Synthesis: Assessing and analyzing integrated audio–video edits and modifications to guarantee the validity of the information
  • FairVoice: An Equitable Audio Deepfake Detector
    Our project, FairVoice, is an equitable audio deepfake detector designed to address this critical gap Our system aims to identify deepfake audio with high accuracy while promoting fairness—reducing the risk that any demographic group is disproportionately misclassified or left more vulnerable
  • Deepfakes And How Do They Affect Cybersecurity
    Regular cybersecurity training and comprehensive cybersecurity risk assessments empower employees to identify suspicious communications, whether they are deepfake videos, audio, or emails Establishing a culture of vigilance is critical in preventing fraudulent video detection failures
  • Can deepfakes manipulate us? Assessing the evidence via a critical . . .
    While not all the deepfakes used in the included studies were available for other researchers to view, it is clear that they varied considerably in terms of resolution, audio quality, accuracy of lip-syncing to voice, level of realism of the faces, and visual artifacts due to deepfake technology
  • Source Tracing of Audio Deepfake Systems - Pindrop
    We evaluate our system on two datasets: the ASVspoof 2019 Logical Access and the Multi-Language Audio Anti-Spoofing Dataset (MLAAD) Results from both experiments demonstrate the robustness of the system to identify the different spoofing attributes of deepfake generation systems
  • Research reveals major vulnerabilities in deepfake detectors
    Deepfakes are artificial intelligence (AI) generated synthetic media that can manipulate images, videos, or audio to create hyper-realistic but false content, raising concerns about misinformation, fraud, and privacy violations





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