Presentation attacks in reverberant conditions

A non-transitory computer-readable medium comprising machine-executable instructions which, when executed by one or more processors, cause the one or more processors to:

• obtain a plurality of training audio signals having corresponding training acoustic impulse responses including at least one single-room training acoustic impulse response and at least one combined multi-room training acoustic impulse response corresponding to the training acoustic impulse responses from two or more rooms;
• train a parameter estimation machine-learning model of a presentation attack detection (PAD) engine to estimate one or more acoustic parameters by executing the parameter estimation machine-learning model of the PAD engine using the training acoustic impulse responses of the plurality of training audio signals and a loss function using a plurality of training labels corresponding to the training audio signals, each training label indicating one or more training acoustic parameters for the training acoustic impulse response in the corresponding training audio signal;
• obtain an audio signal having an acoustic impulse response caused by one or more rooms, the acoustic impulse response of the audio signal including at least one of a single room acoustic impulse response or a combined multi-room acoustic impulse response;
• and
• generate the one or more acoustic parameters for the audio signal by executing the machine-learning model using the audio signal as input.