A Cognitive Model to Mimic an Aspect of Low Level Perception of Sound: Modelling Reverberation Perception by Statistical Signal Analysis

Sound reproduced and perceived in different environments, or transmitted via diverse transmission channels shows distinctive acoustic characteristics, sometimes quoted simply as acoustics. Acoustics of an auditorium can be described by the transfer function from the source to the receiver, or the impulse response in the time domain, which can be measured by instrumentation using a number of methods. On the other hand human listeners, especially trained musicians, sound engineers and acousticians can accurately differentiate acoustics of auditoria by listening to the sound effects, indicating acoustics can be viewed as a lowlevel human perception of sounds. This paper presents a computing model and algorithms to mimic human perception of reverberation, arguably a most significant aspect of acoustic perception. This is done by statistical signal analysis using maximum likelihood estimation with a purposely chosen energy decay model.