Web Audio Pitch Detection for Tuner

Question

So I have been making a simple HTML5 tuner using the Web Audio API. I have it all set up to respond to the correct frequencies, the problem seems to be with getting the actual frequencies. Using the input, I create an array of the spectrum where I look for the highest value and use that frequency as the one to feed into the tuner. The problem is that when creating an analyser in Web Audio it can not become more specific than an FFT value of 2048. When using this if i play a 440hz note, the closest note in the array is something like 430hz and the next value seems to be higher than 440. Therefor the tuner will think I am playing these notes when infact the loudest frequency should be 440hz and not 430hz. Since this frequency does not exist in the analyser array I am trying to figure out a way around this or if I am missing something very obvious.

I am very new at this so any help would be very appreciated.

Thanks

Answer 1

There are a number of approaches to implementing pitch detection . This paper provides a review of them. Their conclusion is that using FFTs may not be the best way to go - however, it's unclear quite what their FFT-based algorithm actually did.

If you're simply tuning guitar strings to fixed frequencies, much simpler approaches exist. Building a fully chromatic tuner that does not know a-priori the frequency to expect is hard.

The FFT approach you're using is entirely possible (I've built a robust musical instrument tuner using this approach that is being used white-label by a number of 3rd parties). However you need a significant amount of post-processing of the FFT data.

To start, you solve the resolution problem using the Short Timer FFT (STFT) - or more precisely - a succession of them. The process is described nicely in this article .

If you intend building a tuner for guitar and bass guitar (and let's face it, everyone who asks the question here is), you'll need t least a 4092-point DFT with overlapping windows in order not to violate the nyquist rate on the bottom E1 string at ~41Hz.

You have a bunch of other algorithmic and usability hurdles to overcome. Not least, perceived pitch and the spectral peak aren't always the same. Taking the spectral peak from the STFT doesn't work reliably (this is also why the basic auto-correlation approach is also broken).