EDIT: It seems that mov_average_expw() function from scikits.timeseries.lib.moving_funcs submodule from SciKits (add-on toolkits that complement SciPy) better suits the wording of your question. To calculate an exponential smoothing of your data with a smoothing factor alpha (it is (1 – alpha) in Wikipedia’s terms): >>> alpha = 0.5 >>> assert 0 < alpha <= 1.0 … Read more
This is quite a good Open Source Project: https://patterns.enm.bris.ac.uk/hpa-software-package It detects chords based on a chromagram – a good solution, breaks down a window of the whole spectrum onto an array of pitch classes (size: 12) with float values. Then, chords can be detected by a Hidden Markov Model. .. should provide you with everything … Read more
This lets you give frequency, duration, and amplitude, and it is 100% .NET CLR code. No external DLL’s. It works by creating a WAV-formatted MemoryStream which is like creating a file in memory only, without storing it to disk. Then it plays that MemoryStream with System.Media.SoundPlayer. using System; using System.Collections.Generic; using System.IO; using System.Linq; using … Read more
My first suggestion is to not do your DSP implementation in Java. My second suggestion would be to roll your own simple DSP implementations yourself in Java. Why not to use Java: I have lots of experience writing DSP code over the last 10+ years… and almost none of the DSP code is in Java… … Read more
I don’t think there is a NumPy function for this particular calculation. Here is how I would write it: def estimated_autocorrelation(x): “”” http://stackoverflow.com/q/14297012/190597 http://en.wikipedia.org/wiki/Autocorrelation#Estimation “”” n = len(x) variance = x.var() x = x-x.mean() r = np.correlate(x, x, mode=”full”)[-n:] assert np.allclose(r, np.array([(x[:n-k]*x[-(n-k):]).sum() for k in range(n)])) result = r/(variance*(np.arange(n, 0, -1))) return result The assert … Read more
Most synthesizers labled ‘FM’ in fact do phase modulation (PM, see https://en.wikipedia.org/wiki/Phase_modulation ). There are some benefits (mostly leading to more stable sound over a large tonal range). The OPL2 may use this too, I found no clear evidence, but the Wikipedia article also uses the term ‘phase modulation’. For short, many musical synthesizers labeled … Read more
Looking at the screenshots of the source audio files, one simple way to detect a change in sound level would be to do a numerical integration of the samples to find out the “energy” of the wave at a specific time. A rough algorithm would be: Divide the samples up into sections Calculate the energy … Read more
The short answer is that you need much more than one algorithm. Good chord recognition methods could more aptly be described as “systems”, but usually they are indeed based on an initial transform to the frequency domain (most often DFT). If you want a chord representaton of the song similar to this C G Am … Read more
This is an old question, but I thought the answer could be improved. Imagine the signal you want to fourier transform is a pure sine wave. In the frequency domain, you would expect it to have a sharp spike only at the frequency of the sine. However if you took the fourier transform, your nice … Read more