Fake Speech Answer-Sheet Detection on Intelligent Learning App Based on Block-Based Deep Neural Network

In order to detect the fake speech answer-sheet obtained by text-to-speech or voice conversion algorithms on intelligent English learning app, this paper proposed the idea of block-based deep neural network (BDNN), which is constructed to extract deep features. It is composed of classification-based blocks. In BDNNs, the deep feature extracted by a preceding block serves as the input to its following block. Different from the commonly used inputs for deep features extraction, the magnitude-phase spectrum, including magnitude and phase information, is exploited to feed BDNNs in order to extract effective deep features. The experimental results show that the proposed method can detect most of fake speech answer-sheet on intelligent English learning app.