freqestimate: fundamental frequency detection

Frequency estimation of a signal with different algorithms

The most important entry point is f0curve(), which estimates the fundamental frequency of an audio signal together with its voicedness (the reliability of the measurement)

Functions

ceil(x, /)	Return the ceiling of x as an Integral.
detectMinFrequency(samples, sr[, ...])	Detect the min.
f0Autocorr(sig, sr)	Estimate frequency using autocorrelation
f0FFT(sig, sr)	Estimate frequency from peak of FFT
f0HPS(sig, sr[, maxharms])	Estimate frequency using harmonic product spectrum (HPS)
f0ZeroCross(sig, sr)	Estimate frequency by counting zero crossings
f0curve(sig, sr[, minfreq, overlap, method, ...])	Estimate the fundamental and its voicedness
f0curvePyin(sig, sr[, minfreq, maxfreq, ...])	Calculate the fundamental based on the pyin method
f0curvePyinVamp(sig, sr[, fftsize, overlap, ...])	Calculate the fundamental using the pyin vamp plugin
frequencyToWindowSize(freq, sr[, powerof2, ...])	Return the size of a window in samples which can fit the given frequency
nextpowerof2(x)	Return the lowest power of two >= x
parabolic(f, x)	Estimates inter-sample maximum