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PODetect beat and play (wav) file in a synchronised manner
 

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    <p>I am trying my hands at Audio Processing in python with <a href="http://archive.gamedev.net/archive/reference/programming/features/beatdetection/index.html" rel="nofollow">this</a> Beat Detection algorithm. I have implemented the first (non-optimized version) from the aforementioned article. While it prints some results, I have no way to detect whether it works with some accuracy or not as I do not know how to play sound with it.</p> <p>Currently, I am using <code>Popen</code> to asynchronously start my media player with the song before going into the computation loop, but I am not sure if this strategy works and is giving synchronous results.</p> <pre><code>#!/usr/bin/python import scipy.io.wavfile, numpy, sys, subprocess # Some abstractions for computation def sumsquared(arr): sum = 0 for i in arr: sum = sum + (i[0] * i[0]) + (i[1] * i[1]) return sum if sys.argv.__len__() &lt; 2: print 'USAGE: wavdsp &lt;wavfile&gt;' sys.exit(1) numpy.set_printoptions(threshold='nan') rate, data = scipy.io.wavfile.read(sys.argv[1]) # Beat detection algorithm begin # the algorithm has been implemented as per GameDev Article # Initialisation data_len = data.__len__() idx = 0 hist_last = 44032 instant_energy = 0 local_energy = 0 le_multi = 0.023219955 # Local energy multiplier ~ 1024/44100 # Play the song p = subprocess.Popen(['audacious', sys.argv[1]]) while idx &lt; data_len - 48000: dat = data[idx:idx+1024] history = data[idx:hist_last] instant_energy = sumsquared(dat) local_energy = le_multi * sumsquared(history) print instant_energy, local_energy if instant_energy &gt; (local_energy * 1.3): print 'Beat' idx = idx + 1024 hist_last = hist_last + 1024 # Right shift history buffer p.terminate() </code></pre> <p>What modification/additions can I make to the script in order to get audio output and the algorithm (console) output in a time synchronised manner? i.e When console outputs result for a particular frame, that frame must be playing on the speakers. </p>
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    1. COYou can rewrite `sumsquared` as one line: `return (arr**2).sum()`. This will push all of those computations down into C code and will probably be much faster.
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