Guitar pitch detection in android

Question

I try to develop a guitar game in android platform.

And I need to do the real-time pitch detection to get the frequency of guitar chord/String.

I will get the input from the microphone, and then analyze the input (the input playing which kind of guitar string/chord)

I find two kinds of method that I can use, one is YIN, another one is FFT.

Which method can get better performance and exact result?

Answer 1

You need to first understand what 'pitch' really is (read the Wikipedia link below). When a single note is made on a guitar or piano, what we hear is not just one frequency of sound vibration, but a composite of multiple sound vibrations occurring at different mathematically related frequencies. The elements of this composite of vibrations at differing frequencies are referred to as harmonics or partials. For instance, if we press the Middle C key on the piano, the individual frequencies of the composite's harmonics will start at 261.6 Hz as the fundamental frequency, 523 Hz would be the 2nd Harmonic, 785 Hz would be the 3rd Harmonic, 1046 Hz would be the 4th Harmonic, etc. The later harmonics are integer multiples of the fundamental frequency, 261.6 Hz ( ex: 2 x 261.6 = 523, 3 x 261.6 = 785, 4 x 261.6 = 1046 ).

Below, at GitHub.com, is the C++ source code for an unusual two-stage algorithm that I devised which can do Realtime Pitch Detection on polyphonic MP3 files while being played on Windows. This free application (PitchScope Player, available on web) is frequently used to detect the notes of a guitar or saxophone solo upon a MP3 recording. You could download the executable for Windows to see my algorithm at work on a mp3 file of your choosing. The algorithm is designed to detect the most dominant pitch (a musical note) at any given moment in time within a MP3 or WAV music file. Note onsets are accurately inferred by a change in the most dominant pitch (a musical note) at any given moment during the MP3 recording.

I use a modified DFT Logarithmic Transform (similar to a FFT) to first detect these possible Harmonics by looking for frequencies with peak levels (see diagram below). Because of the way that I gather data for my modified Log DFT, I do NOT have to apply a Windowing Function to the signal, nor do add and overlap. And I have created the DFT so its frequency channels are logarithmically located in order to directly align with the frequencies where harmonics are created by the notes on a guitar, saxophone, etc.

My Pitch Detection Algorithm is actually a two stage process: a) First the ScalePitch is detected ('ScalePitch' has 12 possible pitch values: {E, F, F#, G, G#, A, A#, B, C, C#, D, D#} ) b) and after ScalePitch is determined, then the Octave is calculated by examining all the harmonics for the 4 possible Octave-Candidate notes. The algorithm is designed to detect the most dominant pitch (a musical note) at any given moment in time within a polyphonic MP3 file. That usually corresponds to the notes of an instrumental solo. Those interested in the C++ source code for my Two Stage Pitch Detection algorithm might want to start at the Estimate_ScalePitch() function within the SPitchCalc.cpp file at GitHub.com.

https://github.com/CreativeDetectors/PitchScope_Player

https://en.wikipedia.org/wiki/Transcription_(music)#Pitch_detection

Below is the image of a Logarithmic DFT (created by my C++ software) for 3 seconds of a guitar solo on a polyphonic mp3 recording. It shows how the harmonics appear for individual notes on a guitar, while playing a solo. For each note on this Logarithmic DFT we can see its multiple harmonics extending vertically, because each harmonic will have the same time-width. After the Octave of the note is determined, then we know the frequency of the Fundamental.

The diagram below demonstrates the Octave Detection algorithm which I developed to pick the correct Octave-Candidate note (that is, the correct Fundamental), once the ScalePitch for that note has been determined. Those wishing to see that method in C++ should go to the Calc_Best_Octave_Candidate() function inside the file called FundCandidCalcer.cpp, which is contained in my source code at GitHub.