A large number of objects are available from Tristan Jehan
for estimating signal parameters and features.
The brightness˜ object (by Tristan Jehan) provides a “brightness” indicator (spectral centroid measure).
The noisiness˜ object (by Tristan Jehan) estimates noise in terms of spectral flatness.
The beat˜ object (by Tristan Jehan) is a signal beat and tempo detector.
Several different options exist for pitch tracking in MSP. Be advised that pitch detection is a difficult and long-running problem in digital audio processing, especially for noisy or polyphonic sounds.
The fzero˜ object is built into Max/MSP and attempts to estimate a fundamental frequency for monophonic signals.
The fiddle˜
object, written by Miller Puckette, provides an estimate of the fundamental frequency and amplitude of an input sound. If specified, it will attempt to track more than one voice at the same time.
The pitch˜ object (by Tristan Jehan) is based on fiddle˜.
More generally, the YIN algorithm
uses autocorrelation to estimate the fundamental frequency of speech or musical sounds.
Trond Lossius
also has a number of Max/MSP objects available free for download.
The tl.envfollow˜ abstraction (from Trond Lossius) will track the amplitude envelope of a signal.