I prefer a Savitzky-Golay filter. It uses least squares to regress a small window of your data onto a polynomial, then uses the polynomial to estimate the point in the center of the window. Finally the window is shifted forward by one data point and the process repeats. This continues until every point has been … Read more
Here is a graphic that illustrates the threshold approach to note onset detection: This image shows a typical WAV file with three discrete notes played in succession. The red line represents a chosen signal threshold, and the blue lines represent note start positions returned by a simple algorithm that marks a start when the signal … Read more
Before we actually go into what that MATLAB command does, you probably want to know what a spectrogram is. That way you’ll get more meaning into how each parameter works. A spectrogram is a visual representation of the Short-Time Fourier Transform. Think of this as taking chunks of an input signal and applying a local … Read more
JLayer should do everything you need. It’s not dead, it’s just stable. The author finished it up quite a long time ago and the MP3 format has not seen much change since. You’ll notice that his MP3SPI codebase is a little more recent. What MP3SPI does, is that translates JLayer’s abilities into JavaSound APIs. Thus … Read more
All the previous answers are correct if you want a technically accurate or scientifically valuable answer. But if you just want a general estimation of comparative loudness, like if you want to check whether the dog is barking or whether a baby is crying and you want to specify the threshold in dB, then it’s … Read more
The array you are showing is the Fourier Transform coefficients of the audio signal. These coefficients can be used to get the frequency content of the audio. The FFT is defined for complex valued input functions, so the coefficients you get out will be imaginary numbers even though your input is all real values. In … Read more
You could skip the use of buttord, and instead just pick an order for the filter and see if it meets your filtering criterion. To generate the filter coefficients for a bandpass filter, give butter() the filter order, the cutoff frequencies Wn=[lowcut, highcut], the sampling rate fs (expressed in the same units as the cutoff … Read more
The complex data is interleaved, with real components at even indices and imaginary components at odd indices, i.e. the real components are at index 2*i, the imaginary components are at index 2*i+1. To get the magnitude of the spectrum at index i, you want: re = fft[2*i]; im = fft[2*i+1]; magnitude[i] = sqrt(re*re+im*im); Then you … Read more
You probably want portable C code here, which your compiler will turn into proper ARM assembly. ARM has conditional moves, and these can be conditional on overflow. The algorithm then becomes: add and conditionally set the destination to unsigned(-1), if overflow was detected. uint16_t add16(uint16_t a, uint16_t b) { uint16_t c = a + b; if … Read more