Digital audio growth made understanding human audition essential

Evidence

There are different motivations for building such models. First of all, being able to model the functionalities of different parts of the system provides basic knowledge of the auditory system. Often, more than one mechanism affects the perceived characteristics of an auditory object, making the analysis of the results of psychoacoustic tests complicated. The complications can be mitigated when the effects of the mechanisms can be isolated in the computational domain, making the interpretation of the results easier. Second, a very important application for such models is the evaluation of audio quality. Modern acoustic systems comprise various transfers in the acoustic, signal processing, and telecommunication domains. The measurement of quality of reproduced audio cannot be performed with simple linear measures, which calls for the usage of models of human hearing for such tasks. Ideally, the fidelity of audio systems could be estimated by computing the auditory cues reaching the conscious level. The third application of auditory models is in the diagnostics of hearing-impaired patients. The symptoms of the patient would be characterized with specific psychoacoustic tests, and the attributes of the model of human hearing were adjusted until the symptoms were explained. Optimally, this would track down the reason for the symptoms. — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 821 (#expands, via linked claim)

An even stronger motivation for modelling hearing computationally originates from the engineering point of view, wherein a functional model enables emulating the functionality of hearing in numerous practical applications, especially if the model runs in real time. Such applications include, for example, speech recognition, sound reproduction, spatial audio techniques, hearing aids, and cochlear implants. Mimicking brain functions in the computational domain is also very educating and an inspiring topic: the human brain is a good engineering solution, and reverse engineering it is a good exercise in signal processing. — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 1564 (#expands, via linked claim)

Categorization

• XREF: connects to: Acoustics, perception, and signal processing underpin sound-technology R&D; Computational auditory models serve knowledge, audio-quality measurement, and diagnostics — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 821; Real-time auditory models enable speech recognition, sound reproduction, and hearing aids — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 1564 (+1 more)

Related

• Computational auditory models serve knowledge, audio-quality measurement, and diagnostics (similarity 0.91)
• Real-time auditory models enable speech recognition, sound reproduction, and hearing aids (similarity 0.91)
• Acoustics, perception, and signal processing underpin sound-technology R&D (similarity 0.90)
• Physically modeling sound sources enables flexible digital instruments (similarity 0.88)
• Computational auditory modelling began only in the 1960s (similarity 0.86)
• Engineering perspectives increasingly serve computational modelling of auditory perception. (similarity 0.86)
• Auditory models link acoustic stimulus features to perceived attributes computationally. (similarity 0.86)
• Higher-level hearing models rely on assumptions tested only against psychoacoustic data (similarity 0.86)
• Computational sound quality models are trained on subjective listening data (similarity 0.85)
• Digital audio’s rise made auditory perception knowledge essential to engineers (similarity 0.84)
• Computational models extract quantitative metrics for the ear’s perceptual dimensions (similarity 0.84)
• Computational auditory scene analysis targets human-level performance without imitating the ear (similarity 0.84)
• Neuron-by-neuron modelling of audition is computationally infeasible now (similarity 0.84)
• Computational simulation is the best method to model the auditory system’s function (similarity 0.84)
• A complete mathematical model of the entire auditory system will never exist (similarity 0.84)

Broader Connections

• Computational auditory models serve knowledge, audio-quality measurement, and diagnostics #expands (0.85) — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 821
• Real-time auditory models enable speech recognition, sound reproduction, and hearing aids #expands (0.80) — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 1564
• Subjective experience dictates which measurements matter in audio research #expands (0.72)