论文标题
CFAD：用于假音频检测的中文数据集
CFAD: A Chinese Dataset for Fake Audio Detection
论文作者
论文摘要
假音频检测是一个日益关注的问题，并且已经为研究设计了一些相关的数据集。但是，在复杂条件下没有中文的标准公共数据集。在本文中，我们旨在填补空白并设计中国假音频检测数据集（CFAD），用于研究更概括的检测方法。十二种主流语音生成技术用于生成假音频。为了模拟现实生活中的场景，选择了三个噪声数据集以添加五个不同的信噪比，并考虑了六个编解码器进行音频转编码（格式转换）。 CFAD数据集不仅可以用于假音频检测，还可以用于检测假言的算法以进行音频取证。基线结果通过分析提出。显示具有概括的伪造音频检测方法的结果仍然具有挑战性。 CFAD数据集可在以下网址公开获取：https：//zenodo.org/record/8122764。
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.
