Practical sound fluctuation models substitute specific-loudness differences for masking-depth values
Evidence
While for most sounds described in this chapter values of .::1L are available this is usually not the case for sounds typical for practical applications. Therefore, a computer program was developed which uses instead of the .::1L values the corresponding differences in specific loudness. — Professor Dr.-Ing. Hugo Fastl, Professor Dr.-Ing. Eberhard, Psychoacoustics- Facts and Models, 1434
Categorization
Category: Factual Claims
- XREF: Specific loudness links back to earlier loudness-model chapters; shows the component reuse across psychoacoustic models.
Related
- Computer models substitute specific loudness differences where masking-depth data are unavailable (similarity 0.92)
- Computerized loudness models track the 1 kHz tone within 2 percent (similarity 0.85)
- A 1 dB level change anchors the model for just-noticeable slow sound variations (similarity 0.82)
- Model-computed and measured loudness match across the full level range (similarity 0.81)
- Amplitude-modulated loudness directly increases perceived fluctuation strength (similarity 0.81)
- Temporal partial masking of loudness is robust across sound types and frequencies (similarity 0.81)
- Adjustment methods bias moderate sounds toward louder settings for good audibility. (similarity 0.80)
- Psychoacoustic loudness models cannot accurately predict individual listener responses (similarity 0.80)
- Loudness models estimate total neural activity since it cannot be measured directly (similarity 0.80)
- A 1 dB level change anchors the model of just-noticeable slow variations. (similarity 0.80)
- Humans detect level changes of about 1 dB at moderate volumes (similarity 0.80)
- A 40-dB level rise increases fluctuation strength by a factor of roughly 2.5 (similarity 0.80)
- A tone and wideband noise of very different levels can equally sound loud (similarity 0.80)
- Specific loudness generalizes beyond loudness to describe sharpness (similarity 0.80)
- Standard loudness analysis discards response variability that probabilistic models can exploit (similarity 0.80)