Introduction The human auditory system is very accurate to discern the content, location and meaning of signals through discrete neural processes. The accuracy of these processes begins with the external anatomical structure of the auditory pathway: the atrial appendages and ear canal. Pinuses are used to collect sounds from the environment and generate direction-dependent cues through spectral transformation (Hofman et al., 1998; Raykar et al., 2005). The sound of the funnel entering the ear canal includes amplification and attenuation of a series of frequencies.
In perception and psychophysics, auditory scene analysis (ASA) is a proposed model for the basis of auditory perception. This is understood as a process by which the human auditory system combines sound into elements that make sense. That word was built by psychologist Albert Bregman. A related concept in machine perception is computational auditory scene analysis (CASA), closely related to sound source separation and blind signal separation. The sound reaches the ear, and the eardrum vibrates as a whole. This signal needs to be analyzed (in some way). The ASA model of Bregman is listened to sound like "integrated" (sounds like the whole - very similar to music's harmony), or "separated" into a single component (resulting in alignment It will sound like it). For example, some people can hear ringtones as "single" sounds (integrated sounds) or they can hear individual voices - they can separate sounds.
A computerized auditory scene analysis (CASA) is a study of auditory scene analysis by calculation means. Basically, the CASA system is a "machine listening" system designed to separate sound source combinations in the same way as human listeners. The difference between CASA and the field of blind signal separation is that it is based (at least to some extent) on the mechanism of the human auditory system and is therefore to use microphone recordings of no more than two acoustic environments . This is related to cocktail party issues.