Audio is one of the most used way of human communication, but at the same
time it can be easily misused by to trick people. With the revolution of AI,
the related technologies are now accessible to almost everyone thus making it
simple for the criminals to commit crimes and forgeries. In this work, we
introduce a deep learning method to develop a classifier that will blindly
classify an input audio as real or mimicked. The proposed model was trained on
a set of important features extracted from a large dataset of audios to get a
classifier that was tested on the same set of features from different audios.
Two datasets were created for this work; an all English data set and a mixed
data set (Arabic and English). These datasets have been made available through
GitHub for the use of the research community at
this https URL. For the purpose of comparison, the audios
were also classified through human inspection with the subjects being the
native speakers. The ensued results were interesting and exhibited formidable
accuracy.

该论文使用深度学习方法建立了一个分类器，用于区分输入音频是否为真实录制，有助于解决 AI 技术使犯罪和伪造更容易的问题。论文中提供了英语和英阿混合语数据集，并对该分类器进行了人工核查以验证其准确性。