counting the number of frequency in wav file
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hi, i would like to count the number of frequency on my sample audio file. it is a recorded drum audio file which contain 8 beat of kick pedal in 7 seconds. so the problem is, how to make a simulation to count the number of kick pedal in this audio file (.wav)
here are my .wav file
[y,fs]=audioread('C:\Users\Faiz\Desktop\Kick.wav');
t=linspace(0,length(y)/fs,length(y));
plot (t,y)
7 Kommentare
Jan
am 24 Apr. 2018
Did you try to attach the file? What do you mean by "simulation"? What does "number of kick pedal" mean - the number of different pedals or the number of hits? What is "number of frequency"? A kick pedal produces a spectrum of frequencies. The number of different frequencies you find in the signal depends on the resolution of the data acquisition. Most likely you will find an amplitude for each signal, which is allowed by the Nyquist theorem and the block width of the FFT analysis.
Pleas edit the question and add more details.
faiz hazizi
am 24 Apr. 2018
Jan
am 25 Apr. 2018
"Upload" would mean, that you have posted the file in this forum such that the readers can try to solve the problem by their own.
You could calculate the RMS (root mean square) of the signal and call findpeaks to determine the number of peaks.
faiz hazizi
am 25 Apr. 2018
Von Duesenberg
am 25 Apr. 2018
From your figure, the approach suggested by Jan seems adequate.
faiz hazizi
am 25 Apr. 2018
Jan
am 26 Apr. 2018
@faiz hazizi: Remember that a diagram without labels does not explain anything. What do the two diagram represent?
The original signal has positive and negative values. You are not interested in the maximum value, but in the maximum amplitude. This can be positive or negative. Using abs helps to move all values to the positive side. If you have a single signal (mono sound), this is exactly the same as RMS: The mean of a scalar is the scalar, and Root of Squared value makes the sign positive. For a stereo signal, RMS considers both channels.
There is no "relationship" between RMS and findpeaks. The first one converts the signal to do what you want, the second one finds the peaks.
"your_signal" is the "y" in your code: The variable in which the audio signal is stored.
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Von Duesenberg
am 25 Apr. 2018
A possible workflow:
%compute the envelope of y (your signal)
%assuming it's mono, and adjust the second
%parameter of the envelope function with
%successive plots of myEnv
[myEnv, ~] = envelope(y, 3000, 'peak');
%apply findpeaks, and adjust 'MinPeakProminence'
%to your needs
[pk, loc] = findpeaks(myEnv, 'MinPeakProminence', .5);
%get the number of peaks
nbPk = length(pk);
6 Kommentare
faiz hazizi
am 26 Apr. 2018
Walter Roberson
am 26 Apr. 2018
Which MATLAB version are you using? Earlier versions of findpeaks did not expect that option.
Von Duesenberg
am 26 Apr. 2018
Bearbeitet: Von Duesenberg
am 26 Apr. 2018
Are you sure your audio is mono? If this is not the case, you should do this instead:
[myEnv, ~] = envelope(y(:,1), 3000, 'peak');
faiz hazizi
am 26 Apr. 2018
Von Duesenberg
am 26 Apr. 2018
Bearbeitet: Von Duesenberg
am 26 Apr. 2018
If you do
size(y)
And the second output says 2, then your audio is stereo; if it says 1, your audio is mono.
Jan
am 26 Apr. 2018
@faiz: "Mono" means, that the sound has been recorded with 1 channel. "Stereo" uses 2 channels, and needs 2 microphones. Ask WikiPedia for details.
If a sound is recorded with 2 channels, the output of audioread must have two columns also. See: doc audioread.
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