Exploration of Source and Filter Information for the Detection of Replay Attacks in Speaker Verification

Abstract

Automatic speaker verification (ASV) is defined as the task of accepting or rejecting an identity claim of a speaker based on their speech. ASV systems are prone to different kinds of spoofing attacks where the system is presented with a spoofed speech signal instead of a speech signal from a genuine speaker. These spoofing attacks can be a serious threat to an ASV system as they can increase false acceptance rates and negatively impact the performance of the system. Hence, it becomes essential to detect these spoofing attacks and protect the security of an ASV system. This thesis deals with a specific kind of spoofing attack called the replay attack. A replay attack is performed by secretly recording the speech of a genuine user of an ASV system and playing it back to the system to obtain unauthorized access.