#Web audio tuner how to#
#Web audio tuner windows#

The data for the algorithm is provided from the sound card capture buffer. New ComplexNumber( 0, alpha * k).PoweredE() ĬomplexNumber oddPart = oddPartMultiplier * data ĭouble spectrogram = new double įor ( int i = 0 i < spectrogram.Length i++) Cooley-Tukey for ( int i = 0 i < bitsInLength i++) The heart of the solution and the SoundAnalysis project is the FFT algorithm (see the Calculate method of the SoundAnalysis.FftAlgorithm class):ĬomplexNumber data = new ComplexNumber

#Web audio tuner windows#

The solution contains three projects: the main windows application ( FftGuitarTuner), the sound analysis library ( SoundAnalysis), and the sound capture library ( SoundCapture). The pitches of the open strings (E2, A2, D3, G3, B3, and E4) are selected in the table in bold. The typical (six string) guitar normally plays pitches of great through two-lined octaves. Traditional Octave Names (Scientific), Hz Table: Notes and Their Fundamental Frequencies Note Name The frequencies of two neighboring notes are different by 2 1/12, and frequencies of the notes with the same name in two neighboring octaves are different by 2. The 'standard pitch' (A one-lined or A4) has a fundamental frequency of its sound waves equals to 440 Hz.

Octaves also have names: great, small, one-lined, two-lined, etc. An octave has 12 named pitches: C (prime), C#, D, D#, E, F, F#, G, G#, A, A#, and B. Traditionally musical alphabet frequencies are divided by octaves, and then by semitones. One of the characteristics of a musical note is a pitch (fundamental frequency). When a note is played on a musical instrument, the sound waves are generated by strings, air, or the speaker - an instrument generates a musical note. The improved algorithm finds several such places, candidate frequency bins, with the magnitude squared in the top of the maximum values, and further analyzes them to verify the candidate fundamental frequencies by using the signal data. After the spectrogram is calculated, the fundamental frequency can be determined by finding the index of the maximum value of the magnitude squared. We will use a Fast Fourier Transform (FFT) to generate the spectrogram of the signal of short periods of time. The result of the STFT can be used to produce the spectrogram of the signal: the magnitude squared over time and frequencies. The Short-Time Fourier Transform (STFT) makes representation of the phase and magnitude of the signal. To determine that, the data need to be analyzed. The digital signal does not provide any information about frequencies that are present in the sound.

A digital signal is a set of quantized sound values that were taken in uniformly spaced times. Modern sound cards can capture digital signals. The computer can capture live sound/music using a microphone that is connected to the sound card.

#Web audio tuner how to#

Also, we will see how to apply the algorithm to analyze live sound to build a simple guitar tuner: the code provides a solution to the problem of calculation of the fundamental frequency of the played pitch. This article shows how to use a Fast Fourier Transform (FFT) algorithm to calculate the fundamental frequency of a captured audio sound.