Instantaneous, Short-Term, and Long-Term Loudness

Finally, Fig.6.8 shows the instantaneous loudness, short-term loudness, and long-term loudness functions overlaid, for the same speech sample used in the previous plots. These are all single-valued functions of time which indicate the relative loudness of the signal on different time scales. See [86] for further discussion. While the lower plot looks reasonable, the upper plot (in sones) predicts only three audible time regions. Evidently, it corresponds to a very low listening level.^7.10

The instantaneous loudness is simply the sum of the specific loudness over all frequencies. The short- and long-term loudnesses are derived by smoothing the instantaneous loudness with respect to time using various psychoacoustically motivated time constants [86]. The smoothing is nonlinear because the loudness tracks a rising amplitude very quickly, while decaying with a slower time constant.^7.11 The loudness of a brief sound is taken to be the local maximum of the short-term loudness curve. The long-term loudness is related to loudness memory over time.

The upper plot gives loudness in sones, which is based on loudness perception experiments [259]; at 1kHz and above, loudness perception is approximately logarithmic above 50 dB SPL or so, while below that, it tends toward being more linear. The lower plot is given in phons, which is simply sound pressure level (SPL) in dB at 1 kHz [259, p. 111]; at other frequencies, the amplitude in phons is defined by following an ``equal-loudness curve'' over to 1 kHz and reading off the level there in dB SPL. This means, e.g., that all pure tones have the same perceived loudness when they are at the same phon level, and the dB SPL at 1 kHz defines the loudness of such tones in phons.

---

Previous: Spectrograms Compared
Next: Summary

Order a Hardcopy of Spectral Audio Signal Processing

---

About the Author: Julius Orion Smith III
Julius Smith's background is in electrical engineering (BS Rice 1975, PhD Stanford 1983). He is presently Professor of Music and Associate Professor (by courtesy) of Electrical Engineering at Stanford's Center for Computer Research in Music and Acoustics (CCRMA), teaching courses and pursuing research related to signal processing applied to music and audio systems. See http://ccrma.stanford.edu/~jos/ for details.