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POFrequency detection from a sound file
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copied!<p>What I am trying to achieve is the following: I need the frequency values of a sound file (.wav) for analysis. I know a lot of programs will give a visual graph (spectrogram) of the values but I need to raw data. I know this can be done with FFT and should be fairly easily scriptable in python but not sure how to do it exactly. So let's say that a signal in a file is .4s long then I would like multiple measurements giving an output as an array for each timepoint the program measures and what value (frequency) it found (and possibly power (dB) too). The complicated thing is that I want to analyse bird songs, and they often have harmonics or the signal is over a range of frequency (e.g. 1000-2000 Hz). I would like the program to output this information as well, since this is important for the analysis I would like to do with the data :)</p> <p>Now there is a piece of code that looked very much like I wanted, but I think it does not give me all the values I want.... (thanks to Justin Peel for posting this to a different question :)) So I gather that I need numpy and pyaudio but unfortunately I am not familiar with python so I am hoping that a Python expert can help me on this?</p> <p>Source Code:</p> <pre><code># Read in a WAV and find the freq's import pyaudio import wave import numpy as np chunk = 2048 # open up a wave wf = wave.open('test-tones/440hz.wav', 'rb') swidth = wf.getsampwidth() RATE = wf.getframerate() # use a Blackman window window = np.blackman(chunk) # open stream p = pyaudio.PyAudio() stream = p.open(format = p.get_format_from_width(wf.getsampwidth()), channels = wf.getnchannels(), rate = RATE, output = True) # read some data data = wf.readframes(chunk) # play stream and find the frequency of each chunk while len(data) == chunk*swidth: # write data out to the audio stream stream.write(data) # unpack the data and times by the hamming window indata = np.array(wave.struct.unpack("%dh"%(len(data)/swidth),\ data))*window # Take the fft and square each value fftData=abs(np.fft.rfft(indata))**2 # find the maximum which = fftData[1:].argmax() + 1 # use quadratic interpolation around the max if which != len(fftData)-1: y0,y1,y2 = np.log(fftData[which-1:which+2:]) x1 = (y2 - y0) * .5 / (2 * y1 - y2 - y0) # find the frequency and output it thefreq = (which+x1)*RATE/chunk print "The freq is %f Hz." % (thefreq) else: thefreq = which*RATE/chunk print "The freq is %f Hz." % (thefreq) # read some more data data = wf.readframes(chunk) if data: stream.write(data) stream.close() p.terminate() </code></pre>

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