Towards Faster End-to-End Data Transmission Over Voice Channels

Weijun Zhang, Hao Han, Mingwei Li, Yulong Tian

Abstract: As new technologies spread, phone fraud crimes have become master strategies to steal money and personal identities. Inspired by website authentication, we propose an end-to-end data modem over voice channels that can transmit the caller’s digital certificate to the callee for verification. Without assistance from telephony providers, it is difficult to carry useful information over voice channels. For example, voice activity detection may quickly classify the encoded signals as non-speech signals and reject the input waveform. To address this problem, we propose a chirp-based modulation method and corresponding demodulator using deep learning technology. We demonstrate that FastDOV works in the real world and outperforms the existing methods in terms of goodput.