Excitation Stimuli For Simultaneous Deconvolution of Room Responses

This paper compares three state-of-the-art stimuli (multitone-pink, MLS, and log-sweep) for the deconvolution of several loudspeaker-room impulse responses using a single time-domain measurement after exciting all the loudspeakers simultaneously. A Bayesian hyper-parameter optimization algorithm constructs the stimulus, where the algorithm optimizes the stimuli parameters by minimizing a {\em time-domain error} between the actual impulse responses and the simultaneously deconvolved responses over a training dataset. Objective results are presented for the various stimuli on a test dataset, whereas subjective tests compare the preference to the excitation stimuli played on all the loudspeakers. Additionally, the robustness of the constructed stimuli to various noises at different signal-to-noise ratios (SNR) is compared in the context of simultaneous deconvolution.