EchoVib: Exploring Voice Authentication via Unique Non-Linear Vibrations of Short Replayed Speech
S Abhishek Anand, Jian Liu, Chen Wang, Maliheh Shirvanian, Nitesh Saxena, Yingying Chen
Abstract
Recent advances in speaker verification and speech processing technology have seen voice authentication being adopted on a wide scale in commercial applications like online banking and customer care support and on devices such as smartphones and IoT voice assistant systems. However, it has been shown that the current voice authentication systems can be ineffective against voice synthesis attacks that mimic a user's voice to high precision. In this work, we suggest a paradigm shift from the traditional voice authentication systems operating in the audio domain but susceptible to speech synthesis attacks (in the same audio domain). We leverage a motion sensor's capability to pick up phonatory vibrations, that can help to uniquely identify a user via voice signatures in the vibration domain. The user's speech is played/echoed back by a device's speaker for a short duration (hence our method is termed EchoVib) and the resulting non-linear phonatory vibrations are picked up by the motion sensor for speaker recognition. The uniqueness of the device's speaker and its accelerometer results in a device-specific fingerprint in response to the echoed speech. The use of the vibration domain and its non-linear relationship with audio allows EchoVib to resist the state-of-the-art voice synthesis attacks, shown to be successful in the audio domain.