Ndtyjky

I'm writing a code to analyse a single audio frequency sung by a voice. I need a way to analyse the frequency of the note. Currently I am using PyAudio to record the audio file, which is stored as a .wav, and then immediately play it back.

import numpy as np

import pyaudio

import wave



# open up a wave

wf = wave.open('file.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)



print(len(data))

print(chunk*swidth)



# 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()

The problem is with the while loop. The condition is never true for some reason. I printed out the two values (len(data) and (chunk*swidth)), and they were 8192 and 4096 respectively. I then tried using 2*chunk*swidth in the while loop, which threw this error:

File "C:UsersOllieDocumentsComputing A Level CApyaudio test.py", line 102, in <module>

data))*window

ValueError: operands could not be broadcast together with shapes (4096,) (2048,)

This function finds the frequency spectrum. I have also included a sine signal and a WAV file sample application:

from scipy import fft, arange

import numpy as np

import matplotlib.pyplot as plt

from scipy.io import wavfile

import os





def frequency_sepectrum(x, sf):

    """

    Derive frequency spectrum of a signal from time domain

    :param x: signal in the time domain

    :param sf: sampling frequency

    :returns frequencies and their content distribution

    """

    x = x - np.average(x)  # zero-centering



    n = len(x)

    print(n)

    k = arange(n)

    tarr = n / float(sf)

    frqarr = k / float(tarr)  # two sides frequency range



    frqarr = frqarr[range(n // 2)]  # one side frequency range



    x = fft(x) / n  # fft computing and normalization

    x = x[range(n // 2)]



    return frqarr, abs(x)





# Sine sample with a frequency of 1hz and add some noise

sr = 32  # sampling rate

y = np.linspace(0, 2*np.pi, sr)

y = np.tile(np.sin(y), 5)

y += np.random.normal(0, 1, y.shape)

t = np.arange(len(y)) / float(sr)



plt.subplot(2, 1, 1)

plt.plot(t, y)

plt.xlabel('t')

plt.ylabel('y')



frq, X = frequency_sepectrum(y, sr)



plt.subplot(2, 1, 2)

plt.plot(frq, X, 'b')

plt.xlabel('Freq (Hz)')

plt.ylabel('|X(freq)|')

plt.tight_layout()





# wav sample from https://freewavesamples.com/files/Alesis-Sanctuary-QCard-Crickets.wav

here_path = os.path.dirname(os.path.realpath(__file__))

wav_file_name = 'Alesis-Sanctuary-QCard-Crickets.wav'

wave_file_path = os.path.join(here_path, wav_file_name)

sr, signal = wavfile.read(wave_file_path)



y = signal[:, 0]  # use the first channel (or take their average, alternatively)

t = np.arange(len(y)) / float(sr)



plt.figure()

plt.subplot(2, 1, 1)

plt.plot(t, y)

plt.xlabel('t')

plt.ylabel('y')



frq, X = frequency_sepectrum(y, sr)



plt.subplot(2, 1, 2)

plt.plot(frq, X, 'b')

plt.xlabel('Freq (Hz)')

plt.ylabel('|X(freq)|')

plt.tight_layout()



plt.show()