Long-term averaging of spectra suppresses random background noise

Evidence

One main advantage of using LTAS is that the spectral features of interest during the steady-state portion of the note are enhanced in the resulting plot by the averaging process with respect to competing acoustic sounds, such as background noise, which change over the period of the LTAS and thus average toward zero. — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 1431

Such average spectra are commonly used for analyzing the frequency components of musical notes, and they are known as “long-term average spectra” or “LTAS.” One main advantage of using LTAS is that the spectral features of interest during the steady-state portion of the note are enhanced in the resulting plot by the averaging process with respect to competing acoustic sounds, such as background noise, which change over the period of the LTAS and thus average toward zero. — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 1431

Categorization

• DEFINE: Explains the mechanism and purpose behind long-term average spectra (LTAS).
• corroborated: 3 independent passages support this claim — David M. Howard, Jamie Angus, Acoustics and Psychoacoustics, 1431
• XREF: connects to: NC contours rate noise but do not guarantee satisfactory spectral quality; Long-term averaging obscures transient attack and release sounds; Octave-band averaging can hide perceptually relevant acoustic variations (+1 more)

Broader Connections

• Long-term averaging obscures transient attack and release sounds #contradicts (0.85)
• Octave-band averaging can hide perceptually relevant acoustic variations #qualifies (0.80)
• Noise suppression algorithms can degrade speech quality in non-stationary noise #complicates (0.75) — Ville Pulkki, Matti Karjalainen, Communication Acoustics- An…, 2452