Read the data of a single channel from a stereo wave file in Python

Question

I have to read the data from just one channel in a stereo wave file in Python. For this I tried it with scipy.io:

import scipy.io.wavfile as wf
import numpy

def read(path):
    data = wf.read(path)
    for frame in data[1]:
        data = numpy.append(data, frame[0])
    return data

But this code is very slow, especially if I have to work with longer files. So does anybody know a faster way to do this? I thought about the standard wave module by using wave.readframes(), but how are the frames stored there?

Answer 1

scipy.io.wavfile.read returns the tuple (rate, data). If the file is stereo, data is a numpy array with shape (nsamples, 2). To get a specific channel, use a slice of data. For example,

rate, data = wavfile.read(path)
# data0 is the data from channel 0.
data0 = data[:, 0]

Answer 2

The wave module returns the frames as a string of bytes, which can be converted to numbers with the struct module. For instance:

def oneChannel(fname, chanIdx):
""" list with specified channel's data from multichannel wave with 16-bit data """
    f = wave.open(fname, 'rb')
    chans = f.getnchannels()
    samps = f.getnframes()
    sampwidth = f.getsampwidth()
    assert sampwidth == 2
    s = f.readframes(samps) #read the all the samples from the file into a byte string
    f.close()
    unpstr = '<{0}h'.format(samps*chans) #little-endian 16-bit samples
    x = list(struct.unpack(unpstr, s)) #convert the byte string into a list of ints
    return x[chanIdx::chans] #return the desired channel

If your WAV file has some other sample size, you can use the (uglier) function in another answer I wrote here.

I've never used scipy's wavfile function so I can't compare speed, but the wave and struct approach I use here has always worked for me.

Answer 3

rate, audio = wavfile.read(path)

audio = np.mean(audio, axis=1)