What type of study is this?

This is a Quantitative Study study.

September 29, 2025Open Access

EnvSDD: Benchmarking Environmental Sound Deepfake Detection

View Full Paper

Ask AI

Bookmark

Authors

The introduction of EnvSDD improves deepfake detection performance in environmental sounds, indicating a significant advance in audio analysis.

Results show that the proposed audio deepfake detection system significantly outperforms existing methods.
EnvSDD comprises 45.25 hours of real audio and 316.74 hours of deepfake audio, thus ensuring diverse evaluation conditions.
This benchmark addresses limitations in current datasets by offering a large scale of varied audio types and conditions.
The system leverages a pre-trained audio foundation model, enhancing its effectiveness in detecting environmental sound deepfakes.

Yin et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark

September 29, 2025Open Access

View Full Paper

Ask AI

Bookmark

Authors

The introduction of EnvSDD improves deepfake detection performance in environmental sounds, indicating a significant advance in audio analysis.

Results show that the proposed audio deepfake detection system significantly outperforms existing methods.
EnvSDD comprises 45.25 hours of real audio and 316.74 hours of deepfake audio, thus ensuring diverse evaluation conditions.
This benchmark addresses limitations in current datasets by offering a large scale of varied audio types and conditions.
The system leverages a pre-trained audio foundation model, enhancing its effectiveness in detecting environmental sound deepfakes.

Yin et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark