Different auditory features require different subsets of model elements and time constants.
Evidence
It should noted that Figure 13.3 shows only an overview of the functional elements, while an actual filter bank model implementation requires detailed design of compatible elements. In addition, some of the elements may be excluded from certain applications. For instance, not all the short time constants are necessary to evaluate loudness, whereas pitch analysis does not benefit from the use of large time constants. — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 1628
Categorization
Category: Factual Claims
Related
- Different hearing tasks exploit different model time constants. (similarity 0.91)
- Filter bank models outperform DFT in mimicking auditory temporal resolution (similarity 0.82)
- Auditory modelling accuracy trades off sharply against computational cost (similarity 0.82)
- Computational models extract quantitative metrics for the ear’s perceptual dimensions (similarity 0.81)
- Computational auditory modelling began only in the 1960s (similarity 0.81)
- Auditory models link acoustic stimulus features to perceived attributes computationally. (similarity 0.81)
- Hearing’s fine frequency resolution may be modeled at coarser steps in practice (similarity 0.81)
- A complete mathematical model of the entire auditory system will never exist (similarity 0.81)
- Human hearing resists linear time-invariant modeling except at the periphery (similarity 0.80)
- A holistic mathematical theory of the full auditory system is unattainable (similarity 0.80)
- Humans cannot reliably report auditory attributes on absolute internal scales. (similarity 0.80)
- Engineering perspectives increasingly serve computational modelling of auditory perception. (similarity 0.80)
- Detecting changes in auditory textures depends mainly on integration time available (similarity 0.80)
- Higher-level hearing models rely on assumptions tested only against psychoacoustic data (similarity 0.80)
- Functional and physiological modeling approaches divide along intended use. (similarity 0.80)