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First thing to mention is that you must have some kind of Machine Learning algorithm to perform your recognition. You might want to use the following - what's yours? Neural Networks (easy to impleme …

Personally, when working with audio signals I use: File metadata and parameters (if there's a calibration associated with it, bit-depth, sampling frequency, etc.) Metrics, such as RMS/peak dBFS level …

If you want to play only one channel then you must set zeros at one of your matrix columns, i.e.: sound_L = sound_array; sound_L(:,2) = 0; sound_R = sound_array; sound_R(:,1) = 0; So your code bec …

One application of the Hilbert Transform is to obtain a so-called Analytic Signal. For signal $s(t)$, its Hilbert Transform $\hat{s}(t)$ is defined as a composition: $$s_A(t)=s(t)+j\hat{s}(t) $$ The …

Any pause can be done by using vector/matrix concatenation. Let's say you want to make a signal with pause of length P after it, then do the following: P = 400; beep = [sound_array; zeros(P, 2)]; N …

I suggest you to do something like (one plot with two curves): figure plot(sound_L(:,1), 'b'); % blue hold on; grid on; % prevent from redrawing and add grid\ plot(sound_R(:,2), 'r'); % red legend({' …

I think you should try MATLAB's scal2frq. You provide the vector of scales, wavelet name and optionally sampling period. This will return vector of pseudo frequencies. In your case that should be som …

I believe that this "color graph" you are looking for is a spectrogram (although it looks to me more like a scalogram, but you did not mentioned wavelets). Let me give you an example in MATLAB of obta …

Something like that should do. Please keep in mind that this code can be further improved by windowing your signal, using decibel scale for spectrum, taking only first half of a spectrum, etc. This is …

I don't really understand what are you trying to achieve with vector B that has 6 elements. Pre-emphasis filter is defined as: $$y[n]=x[n]-\alpha x[n-1]$$ Where $\alpha$ is $0.97$ in your case. Yo …

Well my friend, if you read the following B&K tutorial about the Order Tracking, then you should encounter so called Vold-Kalman Order Filtering. Personally I don't like it (rather prefer Chirp-Fourie …

The rfft function returns complex values ordered in specific way. In order to retrieve the amplitude of your DFT you must take the absolute value of it. Easiest way to do that is to call y_a = np.abs( …

This question is very broad and it is not possible to give a very good answer without even knowing the internals of your system (the type of the network and features make a big difference). However, I …

After taking a closer look at your results, here is what I think. Because you are playing back sinusoid through your speaker you are also observing it's properties. It has some significant harmoni …

Hate to answer this question, but it is a plotting issue, not the actual design problem. Basically, you don't have enough points at low frequencies cause they are spaced linearly and you are plotting …