Tukukkk

I am using following code obtain from Github. This code extract mfccs,chroma, melspectrogram, tonnetz and spectral contrast features give output in form of feat.np. I want to extract some other features like rmse, zerocross but when i add the relevent code i give error while concatenation.

# coding= UTF-8

#

# Author: Fing

# Date  : 2017-12-03

#



import glob

import os

import librosa

import numpy as np

import matplotlib.pyplot as plt

from matplotlib.pyplot import specgram

import soundfile as sf



def extract_feature(file_name):

    X, sample_rate = sf.read(file_name, dtype='float32')

    if X.ndim > 1:

        X = X[:,0]

    X = X.T



    # short term fourier transform

    stft = np.abs(librosa.stft(X))



    # mfcc

    mfccs = np.mean(librosa.feature.mfcc(y=X, sr=sample_rate, n_mfcc=40).T,axis=0)



    # chroma

    chroma = np.mean(librosa.feature.chroma_stft(S=stft, sr=sample_rate).T,axis=0)



    # melspectrogram

    mel = np.mean(librosa.feature.melspectrogram(X, sr=sample_rate).T,axis=0)



    # spectral contrast

    contrast = np.mean(librosa.feature.spectral_contrast(S=stft, sr=sample_rate).T,axis=0)



    tonnetz = np.mean(librosa.feature.tonnetz(y=librosa.effects.harmonic(X), sr=sample_rate).T,axis=0)



    return mfccs,chroma,mel,contrast,tonnetz



def parse_audio_files(parent_dir,sub_dirs,file_ext='*.wav'):

    features, labels = np.empty((0,193)), np.empty(0)

    for label, sub_dir in enumerate(sub_dirs):

        for fn in glob.glob(os.path.join(parent_dir, sub_dir, file_ext)):

            try:

                mfccs, chroma, mel, contrast,tonnetz = extract_feature(fn)

            except Exception as e:

                print("[Error] extract feature error. %s" % (e))

                continue

            ext_features = np.hstack([mfccs,chroma,mel,contrast,tonnetz])

            print(ext_features)

            print(features)

            features = np.vstack([features,ext_features])

            # labels = np.append(labels, fn.split('/')[1])

            labels = np.append(labels, label)

        print("extract %s features done" % (sub_dir))

    return np.array(features), np.array(labels, dtype = np.int)



def one_hot_encode(labels):

    n_labels = len(labels)

    n_unique_labels = len(np.unique(labels))

    one_hot_encode = np.zeros((n_labels,n_unique_labels))

    one_hot_encode[np.arange(n_labels), labels] = 1

    return one_hot_encode



# Get features and labels

r = os.listdir("data/")

r.sort()

features, labels = parse_audio_files('data', r)

np.save('feat.npy', features)

np.save('label.npy', labels)

 `

This code work fine but when i want to extract other features also like rmse,zero crossing rate etc . when i add

#rmse=np.mean(librosa.feature.rmse(y=X).T,axis=0)

i got following error

File "C:UsersHPAnaconda2libsite-packagesnumpycoreshape_base.py", line 237, in vstack

    return _nx.concatenate([atleast_2d(_m) for _m in tup], 0)



ValueError: all the input array dimensions except for the concatenation axis must match exactly

how i can extract other features and concatenate also.

The shape of STFT and RMSE are different than MFCC and other features. STFT and MFCC are 2 dimensional while the others are one dimensional features.