Python change pitch of wav file [closed]

Question

I need any python library to change pitch of my wav file without any raw audio data processing. I spent couple hours to find it, but only found some strange raw data processing code snippets and video, that shows real-time pitch shift, but without source code.

Answer 1

I recommend trying Librosa's pitch shift function: https://librosa.github.io/librosa/generated/librosa.effects.pitch_shift.html

import librosa
y, sr = librosa.load('your_file.wav', sr=16000) # y is a numpy array of the wav file, sr = sample rate
y_shifted = librosa.effects.pitch_shift(y, sr, n_steps=4) # shifted by 4 half steps

Answer 2

Since a wav file basically is raw audio data, you won't be able to change the pitch without "raw audio processing".

Here is what you could do. You will need the wave (standard library) and numpy modules.

import wave
import numpy as np

Open the files.

wr = wave.open('input.wav', 'r')
# Set the parameters for the output file.
par = list(wr.getparams())
par[3] = 0  # The number of samples will be set by writeframes.
par = tuple(par)
ww = wave.open('pitch1.wav', 'w')
ww.setparams(par)

The sound should be processed in small fractions of a second. This cuts down on reverb. Try setting fr to 1; you'll hear annoying echos.

fr = 20
sz = wr.getframerate()//fr  # Read and process 1/fr second at a time.
# A larger number for fr means less reverb.
c = int(wr.getnframes()/sz)  # count of the whole file
shift = 100//fr  # shifting 100 Hz
for num in range(c):

Read the data, split it in left and right channel (assuming a stereo WAV file).

    da = np.fromstring(wr.readframes(sz), dtype=np.int16)
    left, right = da[0::2], da[1::2]  # left and right channel

Extract the frequencies using the Fast Fourier Transform built into numpy.

    lf, rf = np.fft.rfft(left), np.fft.rfft(right)

Roll the array to increase the pitch.

    lf, rf = np.roll(lf, shift), np.roll(rf, shift)

The highest frequencies roll over to the lowest ones. That's not what we want, so zero them.

    lf[0:shift], rf[0:shift] = 0, 0

Now use the inverse Fourier transform to convert the signal back into amplitude.

    nl, nr = np.fft.irfft(lf), np.fft.irfft(rf)

Combine the two channels.

    ns = np.column_stack((nl, nr)).ravel().astype(np.int16)

Write the output data.

    ww.writeframes(ns.tostring())

Close the files when all frames are processed.

wr.close()
ww.close()