CFAD: A Chinese Dataset for Fake Audio Detection
Abstract
Fake audio detection is a growing concern and some relevant datasets have been designed for research. However, there is no standard public Chinese dataset under complex conditions.In this paper, we aim to fill in the gap and design a Chinese fake audio detection dataset (CFAD) for studying more generalized detection methods. Twelve mainstream speech-generation techniques are used to generate fake audio. To simulate the real-life scenarios, three noise datasets are selected for noise adding at five different signal-to-noise ratios, and six codecs are considered for audio transcoding (format conversion). CFAD dataset can be used not only for fake audio detection but also for detecting the algorithms of fake utterances for audio forensics. Baseline results are presented with analysis. The results that show fake audio detection methods with generalization remain challenging. The CFAD dataset is publicly available at: https://zenodo.org/record/8122764.
Cite
@article{arxiv.2207.12308,
title = {CFAD: A Chinese Dataset for Fake Audio Detection},
author = {Haoxin Ma and Jiangyan Yi and Chenglong Wang and Xinrui Yan and Jianhua Tao and Tao Wang and Shiming Wang and Ruibo Fu},
journal= {arXiv preprint arXiv:2207.12308},
year = {2023}
}
Comments
FAD renamed as CFAD