Welcome to Karadeniz
Technical University Cyber Security
Research Group
Audio forgery data set
created for research project 122E013 and funded by the TUBÝTAK ARDEB 1001
Scientific and Technological Research Projects Support Program. You can find additional info about audios in the dataset.
The KtuArabicForgeryDataset used in the training and testing of the graph-based method, together with the KtuTimitForgeryDataset , has been made available for sharing.
Papers under 122E013 Project
- A novel audio copy move forgery detection method with classification of graph-based representations, 2025
- KTUCengAudioForgerySet: A new Audio Copy-Move Forgery Dataset, 2024, Dataset
- Mel spectrogram-based audio forgery detection using CNN, 2024, Dataset, Test set
- Audio forgery detection and localization with super-resolution spectrogram and keypoint-based clustering approach, 2024
- Multi pattern features based spoofing detection mechanism using one class learning, 2024
- Detection of audio copy-move-forgery with novel feature matching on Mel spectrogram, 2023
- Robust copy-move detection in digital audio forensics based on pitch and modified discrete cosine transform, 2022, Dataset
- Copy-Move Audio Forgery Detection with Instantaneous Frequency, 2024
- Detecting Audio Forgery with Rasta -PLP Rasta-PLP, 2024
- Audio Forgery Detection Method with Mel Spectrogram, 2024
- Deepfake audio detection with vision transformer-based method, 2023
- Robust Audio Forgery Detection Method Based on Capsule Network, 2023
- Forge Audio Detection Using Keypoint Features on Mel Spectrograms, 2022
- Block-Based Forgery Detection with Binary Gradient Model, 2022
- Localization of Forgery on Audio Clips Using GLCM Features and Mel Spectograms, 2022