ZeroCR

ZeroCR/ZeroCR.py

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+import math
+import numpy as np
+
+def ZeroCR(waveData,frameSize,overLap):
+    wlen = len(waveData)
+    step = frameSize - overLap
+    frameNum = int(math.ceil(wlen*1.0/step))
+    zcr = np.zeros((frameNum,1))
+    for i in range(frameNum):
+        curFrame = waveData[np.arange(i*step, min(i*step+frameSize,wlen))]
+        #To avoid DC bias, usually we need to perform mean subtraction on each frame
+        curFrame = curFrame - np.mean(curFrame) # zero-justified
+        zcr[i] = sum(curFrame[0:-1]*curFrame[1:]<=0)
+    return zcr

ZeroCR/ZeroCRTest.py

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+import wave
+import numpy as np
+import pylab as pl
+import ZeroCR
+
+# read wave file and get parameters.
+fw = wave.open('../sounds/aeiou.wav','rb')
+params = fw.getparams()
+print(params)
+nchannels, sampwidth, framerate, nframes = params[:4]
+strData = fw.readframes(nframes)
+waveData = np.fromstring(strData, dtype=np.int16)
+waveData = waveData*1.0/max(abs(waveData))  # normalization
+fw.close()
+
+# calculate Zero Cross Rate
+frameSize = 256
+overLap = 0
+zcr = ZeroCR.ZeroCR(waveData,frameSize,overLap)
+
+# plot the wave
+time = np.arange(0, len(waveData)) * (1.0 / framerate)
+time2 = np.arange(0, len(zcr))*(len(waveData)*1.0/len(zcr)/framerate)
+pl.subplot(211)
+pl.plot(time, waveData)
+pl.ylabel("Amplitude")
+
+pl.subplot(212)
+pl.plot(time2, zcr)
+pl.ylabel("ZCR")
+pl.xlabel("time (seconds)")
+pl.savefig("ZeroCR.png")
+pl.show()