# Re: Robust method of fundamental frequency estimation.

Fundamentally, the problem is that only periodic sounds have a fundamental frequency. For most musical notes, and especially for pianos, deviations from periodic are substantial, which means that all methods are approximations to something that doesn't quite exist. An alternative to an F0 estimation model would be a pitch estimation model; same problems, but at least pitch "exists" as a psychophysical measure.

As Kelly Fritz points out, the "stretched" partials of piano notes needs to be carefully considered. You might want a "fundamental" approximately consistent with some range of partials, or you might want to filter those out and look for an actual lowest frequency. Depends on what you're trying to do.

I'm sorry I don't have a more constructive suggestion handy. In general, I would expect autocorrelation methods to be the place to look, but when you say "THE autocorrelation method" you need to be more explicit about exactly what you've tried and what problems you ran into, and what you're trying to achieve.

`Dick`

At 5:11 PM +0000 1/31/07, Roisin Loughran wrote:
`Dear list,`

I was wondering if any of you know the most robust way to calculate the fundamental frequency of a note across the range of a variety of instruments?

I'm currently working on a matlab program and have tried using the auto-correlation method and the cepstrum method but have found that these both have difficulty in calculating f0 of timbre-rich tones such as those from a piano - particularly in the lower pitch ranges. Does anyone know of a method that is more reliable in these regions or is it necessary that I investigate such complex tones by a different means? From examining a number of the FFTs from these signals it is tempting to just pick the first strongest partial - the complex overtones just seem to confuse the more complicated algorithms, but I realise that this is hardly a reliable approach.

```Any suggestion would be greatly appreciated,

`Roisin Loughran`

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