Gfyuki

I am extracting audio features from wav file by using PLP , By executing this program i am facing this error , kindly help to solve out.

File "C:ProgramDataAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 704, in runfile
execfile(filename, namespace)

File "C:ProgramDataAnaconda3libsite-packagesspyder_kernelscustomizespydercustomize.py", line 108, in execfile
exec(compile(f.read(), filename, 'exec'), namespace)

File "C:/Speech_Processing/2-Speech_Signal_Processing_and_Classification-master/feature_extraction_techniques/plp.py", line 54, in
main()

File "C:/Speech_Processing/2-Speech_Signal_Processing_and_Classification-master/feature_extraction_techniques/plp.py", line 52, in main
PLP()

File "C:/Speech_Processing/2-Speech_Signal_Processing_and_Classification-master/feature_extraction_techniques/plp.py", line 38, in PLP
plp_features = plp(signal,rasta=True)

File "C:ProgramDataAnaconda3libsite-packagessidekitfrontendfeatures.py", line 921, in plp
powspec, log_energy = power_spectrum(input_sig, fs, nwin, shift, prefac)

File "C:ProgramDataAnaconda3libsite-packagessidekitfrontendfeatures.py", line 399, in power_spectrum
ahan = framed[start:stop, :] * window

ValueError: operands could not be broadcast together with shapes (400,2) (400,)

#!usr/bin/python

import numpy.matlib

import scipy

from scipy.fftpack.realtransforms import dct

from sidekit.frontend.vad import pre_emphasis

from sidekit.frontend.io import *

from sidekit.frontend.normfeat import *

from sidekit.frontend.features import *

import scipy.io.wavfile as wav

import numpy as np







def readWavFile(wav):

        #given a path from the keyboard to read a .wav file

        #wav = raw_input('Give me the path of the .wav file you want to read: ')

        inputWav = 'C:/Speech_Processing/2-Speech_Signal_Processing_and_Classification-master/feature_extraction_techniques'+wav

        return inputWav

#reading the .wav file (signal file) and extract the information we need

def initialize(inputWav):

        rate , signal  = wav.read(readWavFile(inputWav)) # returns a wave_read object , rate: sampling frequency

        sig = wave.open(readWavFile(inputWav))

        # signal is the numpy 2D array with the date of the .wav file

        # len(signal) number of samples

        sampwidth = sig.getsampwidth()

        print ('The sample rate of the audio is: ',rate)

        print ('Sampwidth: ',sampwidth)

        return signal ,  rate

def PLP():

        folder = input('Give the name of the folder that you want to read data: ')

        amount = input('Give the number of samples in the specific folder: ')

        for x in range(1,int(amount)+1):

                wav = '/'+folder+'/'+str(x)+'.wav'

                print (wav)

                #inputWav = readWavFile(wav)

                signal,rate = initialize(wav)

                #returns PLP coefficients for every frame

                plp_features = plp(signal,rasta=True)

                meanFeatures(plp_features[0])

#compute the mean features for one .wav file (take the features for every frame and make a mean for the sample)

def meanFeatures(plp_features):

        #make a numpy array with length the number of plp features

        mean_features=np.zeros(len(plp_features[0]))

        #for one input take the sum of all frames in a specific feature and divide them with the number of frames

        for x in range(len(plp_features)):

                for y in range(len(plp_features[x])):

                        mean_features[y]+=plp_features[x][y]

        mean_features = (mean_features / len(plp_features))

        print (mean_features)



def main():

        PLP()



main()