Masked sound components are perceptually ignored within complex sounds

Evidence

The masking effect of individual components in musical sounds, which are complex, with many spectral components, can be determined in terms of the masking effect of individual components on other components in the sound. If a component is completely masked by another component in the sound, the masked component makes no contribution to the perceived nature of the sound itself and is therefore effectively ignored. If the masker is broadband noise, or “white noise,” then components at all frequencies are masked in an essentially linear fashion (i.e., a 10 dB increase in the level of the noise increases the masking effect by 10 dB at all frequencies). — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 1603

Categorization

• XREF: Directly relevant to the reader’s purpose — explains why we hear only prominent spectral peaks in orchestration and mix design. — connects to: Timbre perception can be analyzed through component-to-component masking interactions
• DEFINE: Clarifies the concept of masking applied to complex musical sounds component-by-component.

Related

• Timbre perception can be analyzed through component-to-component masking interactions (similarity 0.89)
• Masked spectral components do not contribute to perceived timbre (similarity 0.88)
• Masking noise prevents listeners from using unintended spectral cues (similarity 0.88)
• Auditory filters are analyzed one component at a time to build up complex effects (similarity 0.85)
• Three acoustic properties determine whether a sound masks another. (similarity 0.84)
• Partially masked sounds have a reduced loudness range in both time and spectrum (similarity 0.83)
• Masked audio components below the masking threshold need no bits transmitted (similarity 0.83)
• Music’s dense spectrum masks its own distortion products. (similarity 0.83)
• Simultaneous-masking filters may understate the ear’s true spectral resolution (similarity 0.83)
• A masker’s intensity, frequency content, and temporal pattern determine its masking capability. (similarity 0.83)
• One sound can mask another even when their spectra do not overlap. (similarity 0.82)
• Masking acts within critical bandwidths, leaving distant-frequency sounds unaffected (similarity 0.82)
• Masking is quantified by the shift in a listener’s hearing-threshold curve (similarity 0.82)
• Orchestral accompaniment masks the voice’s fine spectral detail in recordings (similarity 0.82)
• Masking depends on acoustic relationships between masker and signal, not on subjective noise. (similarity 0.82)