Microphone Identification Using Higher-Order Statistics
This paper presents statistical framework for microphone identification using digital audio recording alone. To accomplish this task, the microphone induced artifacts are modeled using a nonlinear function and then statistical tool based on higher order s
Click to purchase paper as a non-member or login as an AES member. If your company or school subscribes to the E-Library then switch to the institutional version. If you are not an AES member and would like to subscribe to the E-Library then Join the AES!
This paper costs $33 for non-members and is temporarily free for AES members.