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audio-stats's Introduction

Features of the dataset:

spectrum,mean_frequency,peak_frequency,frequencies_std,amplitudes_cum_sum,
mode_frequency,median_frequency,frequencies_q25,frequencies_q75,iqr,
freqs_skewness,freqs_kurtosis,spectral_entropy,
spectral_flatness,spectral_centroid,spectral_spread,spectral_rolloff,
energy,rms,zcr,spectral_mean,spectral_rms,spectral_std,spectral_variance,
meanfun,minfun,maxfun,meandom,mindom,maxdom,dfrange,modindex,bit_rate

spectrum features
signal,mfcc,imfcc,bfcc,lfcc,lpc,lpcc,msrcc,ngcc,psrcc,plp,rplp,gfcc

rows with the asterisk (*) have all the features WITH the bit_rate, all rows without the asterisk (*) have no bit_rate feature

  • 1: normal data without any normalization or resampling applied
  • 2: data with resampled (lowered) bit rate
  • 3: data with loud normalization applied

Here the synthetic technique where the bit_rate is not discriminating

# #
SYSTEM ID A01-A06
Speakers LA_0069, LA_0070, LA_0071, LA_0072, LA_0073, LA_0074, LA_0075
SYSTEM ID A07, A08, A09, A10, A11, A12, A13, A14, A15, A16, A17, A18, A19
Speakers LA_0012, LA_0013, LA_0047, LA_0023, LA_0038

Accuracy of the related models with 10 iterations (the accuracy is the average of the 10 iterations).

Model A01 A02 A03 A04 A05 A06 A07 A08 A09 A10 A11 A12 A13 A14 A15 A16 A17 A18 A19
CART 1 0.929 0.998 1.0 0.849 0.947 0.759 0.871 0.911 0.938 0.892 0.856 0.896 0.987 0.905 0.844 0.773 0.761 0.920 0.697
CART 1* 0.951 0.998 1.0 0.890 0.937 0.790 0.957 0.951 0.972 0.954 0.938 0.908 0.996 0.954 0.896 0.795 0.776 0.911 0.737
CART 2 0.930 1.0 1.0 0.855 0.954 0.790 0.847 0.905 0.957 0.874 0.874 0.914 0.984 0.905 0.831 0.801 0.822 0.917 0.694
CART 2* 0.930 0.999 1.0 0.888 0.938 0.799 0.948 0.911 0.978 0.951 0.920 0.932 0.993 0.899 0.902 0.782 0.767 0.923 0.694
CART 3 0.936 0.999 1.0 0.867 0.954 0.806 0.871 0.935 0.957 0.896 0.877 0.926 0.990 0.944 0.853 0.831 0.764 0.908 0.697
CART 3* 0.972 1.0 1.0 0.892 0.959 0.799 0.975 0.932 0.954 0.966 0.957 0.899 0.990 0.981 0.935 0.798 0.795 0.908 0.730
SVM 1 0.270 0.927 0.894 0.762 0.903 0.406 0.455 0.489 0.801 0.623 0.694 0.755 0.584 0.706 0.639 0.406 0.544 0.834 0.519
SVM 1* 0.856 0.970 0.807 0.803 0.908 0.711 0.932 0.868 0.865 0.954 0.932 0.810 0.957 0.914 0.874 0.813 0.596 0.828 0.498
SVM 2 0.655 0.982 0.883 0.760 0.909 0.709 0.522 0.553 0.740 0.452 0.697 0.773 0.691 0.697 0.507 0.486 0.577 0.880 0.568
SVM 2* 0.843 0.831 0.823 0.823 0.884 0.681 0.908 0.810 0.825 0.914 0.923 0.776 0.914 0.840 0.840 0.611 0.498 0.880 0.461
SVM 3 0.721 0.956 0.922 0.772 0.927 0.458 0.602 0.489 0.779 0.501 0.727 0.755 0.691 0.581 0.574 0.532 0.385 0.816 0.562
SVM 3* 0.874 0.973 0.922 0.816 0.920 0.741 0.932 0.785 0.825 0.948 0.920 0.810 0.975 0.938 0.892 0.819 0.611 0.856 0.590
LR 1 0.737 0.992 0.886 0.759 0.873 0.712 0.724 0.798 0.752 0.651 0.672 0.785 0.914 0.862 0.593 0.651 0.636 0.874 0.581
LR 1* 0.933 0.919 0.877 0.877 0.860 0.704 0.960 0.944 0.923 0.969 0.975 0.905 0.975 0.932 0.883 0.813 0.596 0.847 0.617
LR 2 0.737 0.993 0.875 0.761 0.868 0.729 0.547 0.721 0.712 0.629 0.752 0.767 0.917 0.807 0.611 0.614 0.654 0.886 0.541
LR 2* 0.866 0.850 0.863 0.859 0.915 0.703 0.917 0.856 0.785 0.908 0.935 0.865 0.960 0.865 0.828 0.785 0.596 0.892 0.645
LR 3 0.795 0.997 0.919 0.783 0.927 0.720 0.639 0.795 0.782 0.636 0.721 0.743 0.914 0.840 0.629 0.691 0.602 0.813 0.535
LR 3* 0.952 0.926 0.931 0.886 0.923 0.736 0.981 0.862 0.788 0.990 0.966 0.859 0.978 0.966 0.926 0.847 0.629 0.859 0.645
KNN 1 0.758 0.880 0.929 0.727 0.831 0.695 0.654 0.626 0.831 0.663 0.681 0.807 0.779 0.685 0.525 0.629 0.709 0.874 0.541
KNN 1* 0.924 0.778 0.912 0.863 0.753 0.707 0.941 0.892 0.905 0.954 0.938 0.850 0.941 0.914 0.865 0.779 0.587 0.813 0.614
KNN 2 0.759 0.878 0.929 0.749 0.851 0.697 0.620 0.651 0.801 0.666 0.709 0.792 0.782 0.712 0.581 0.574 0.688 0.859 0.559
KNN 2* 0.864 0.781 0.913 0.837 0.725 0.692 0.923 0.819 0.896 0.917 0.948 0.877 0.941 0.837 0.816 0.730 0.599 0.868 0.605
KNN 3 0.732 0.882 0.959 0.757 0.862 0.687 0.672 0.660 0.785 0.724 0.678 0.755 0.810 0.703 0.550 0.602 0.633 0.825 0.544
KNN 3* 0.934 0.768 0.946 0.858 0.751 0.707 0.944 0.804 0.792 0.966 0.941 0.828 0.972 0.948 0.899 0.761 0.584 0.859 0.593
GMM 1 0.287 0.749 0.685 0.331 0.287 0.712 0.608 0.522 0.529 0.333 0.507 0.489 0.428 0.538 0.547 0.498 0.507 0.480 0.510
GMM 1* 0.320 0.358 0.916 0.314 0.672 0.302 0.366 0.486 0.538 0.324 0.672 0.152 0.058 0.568 0.584 0.360 0.532 0.492 0.522
GMM 2 0.393 0.726 0.331 0.270 0.729 0.270 0.360 0.495 0.470 0.394 0.504 0.492 0.535 0.535 0.464 0.449 0.495 0.483 0.507
GMM 2* 0.626 0.342 0.751 0.430 0.707 0.691 0.633 0.428 0.510 0.327 0.663 0.336 0.593 0.477 0.486 0.513 0.425 0.480 0.483
GMM 3 0.597 0.137 0.769 0.628 0.720 0.296 0.559 0.467 0.718 0.522 0.581 0.443 0.504 0.483 0.513 0.529 0.541 0.489 0.498
GMM 3* 0.684 0.262 0.327 0.689 0.335 0.709 0.648 0.547 0.501 0.308 0.709 0.131 0.152 0.834 0.434 0.660 0.538 0.431 0.525
LDA 1 0.889 0.981 0.991 0.859 0.917 0.741 0.892 0.929 0.914 0.908 0.868 0.883 0.969 0.941 0.844 0.779 0.773 0.951 0.675
LDA 1* 0.947 0.986 0.999 0.885 0.923 0.773 0.966 0.966 0.987 0.975 0.966 0.850 0.990 0.987 0.914 0.862 0.828 0.951 0.721
LDA 2 0.891 0.982 0.993 0.864 0.912 0.778 0.926 0.923 0.963 0.892 0.868 0.926 0.981 0.782 0.767 0.807 0.779 0.938 0.675
LDA 2* 0.907 0.983 0.996 0.891 0.930 0.795 0.960 0.926 0.993 0.960 0.957 0.960 0.981 0.938 0.908 0.856 0.788 0.938 0.666
LDA 3 0.930 0.975 0.991 0.897 0.922 0.800 0.850 0.957 0.981 0.954 0.920 0.951 0.984 0.954 0.874 0.807 0.788 0.932 0.727
LDA 3* 0.964 0.982 0.998 0.922 0.938 0.805 0.984 0.972 0.978 0.975 0.984 0.966 0.993 0.981 0.941 0.914 0.819 0.948 0.773
SVC1 1 0.712 0.712 0.712 0.712 0.712 0.712 0.474 0.522 0.529 0.492 0.507 0.489 0.498 0.538 0.492 0.504 0.507 0.510 0.516
SVC1 1* 0.706 0.706 0.706 0.706 0.706 0.706 0.483 0.507 0.538 0.501 0.516 0.532 0.492 0.431 0.538 0.449 0.495 0.498 0.501
SVC1 2 0.729 0.729 0.729 0.729 0.729 0.729 0.486 0.477 0.470 0.498 0.504 0.492 0.535 0.535 0.483 0.519 0.495 0.474 0.507
SVC1 2* 0.705 0.705 0.705 0.705 0.705 0.705 0.519 0.458 0.510 0.477 0.519 0.458 0.474 0.501 0.510 0.467 0.507 0.519 0.507
SVC1 3 0.720 0.720 0.720 0.720 0.720 0.720 0.440 0.513 0.510 0.522 0.501 0.455 0.504 0.535 0.513 0.529 0.541 0.495 0.495
SVC1 3* 0.724 0.724 0.724 0.724 0.724 0.724 0.483 0.486 0.501 0.532 0.480 0.489 0.510 0.504 0.535 0.516 0.519 0.492 0.461
SVC2 1 0.864 0.992 0.894 0.827 0.932 0.714 0.740 0.847 0.880 0.819 0.773 0.798 0.926 0.859 0.758 0.700 0.733 0.859 0.593
SVC2 1* 0.945 0.995 0.903 0.882 0.925 0.742 0.957 0.957 0.957 0.966 0.978 0.920 0.969 0.948 0.892 0.831 0.697 0.840 0.642
SVC2 2 0.866 0.993 0.887 0.825 0.921 0.729 0.718 0.813 0.889 0.779 0.785 0.825 0.941 0.844 0.706 0.663 0.700 0.892 0.556
SVC2 2* 0.895 0.996 0.883 0.876 0.930 0.720 0.923 0.889 0.972 0.917 0.954 0.926 0.960 0.905 0.850 0.801 0.712 0.877 0.645
SVC2 3 0.851 0.997 0.926 0.843 0.943 0.720 0.764 0.828 0.883 0.792 0.798 0.850 0.935 0.844 0.740 0.691 0.709 0.810 0.522
SVC2 3* 0.959 0.995 0.943 0.888 0.935 0.768 0.981 0.899 0.917 0.981 0.969 0.905 0.978 0.960 0.932 0.825 0.703 0.877 0.657
GPC 1 0.287 0.287 0.287 0.287 0.287 0.287 0.474 0.522 0.529 0.492 0.507 0.489 0.498 0.538 0.492 0.504 0.507 0.510 0.516
GPC 1* 0.293 0.293 0.293 0.293 0.293 0.293 0.483 0.507 0.538 0.501 0.516 0.532 0.492 0.568 0.538 0.550 0.495 0.498 0.501
GPC 2 0.270 0.270 0.270 0.270 0.270 0.270 0.486 0.480 0.470 0.498 0.504 0.492 0.535 0.535 0.483 0.519 0.495 0.474 0.507
GPC 2* 0.294 0.294 0.294 0.294 0.294 0.294 0.519 0.541 0.510 0.477 0.519 0.541 0.474 0.501 0.510 0.467 0.507 0.519 0.507
GPC 3 0.279 0.279 0.279 0.279 0.279 0.279 0.559 0.516 0.510 0.522 0.501 0.455 0.504 0.535 0.513 0.529 0.541 0.495 0.495
GPC 3* 0.275 0.275 0.275 0.275 0.275 0.275 0.483 0.486 0.501 0.532 0.480 0.489 0.510 0.504 0.535 0.516 0.519 0.492 0.461
RFC 1 0.858 0.991 0.972 0.724 0.942 0.736 0.730 0.944 0.908 0.871 0.874 0.905 0.972 0.892 0.770 0.788 0.779 0.896 0.666
RFC 1* 0.864 0.996 0.974 0.729 0.931 0.719 0.957 0.966 0.935 0.831 0.935 0.926 0.993 0.926 0.819 0.850 0.810 0.905 0.672
RFC 2 0.844 0.946 0.966 0.746 0.867 0.731 0.862 0.868 0.917 0.804 0.868 0.914 0.938 0.926 0.801 0.785 0.773 0.926 0.651
RFC 2* 0.867 0.978 0.965 0.779 0.907 0.729 0.889 0.896 0.948 0.899 0.911 0.911 0.978 0.911 0.834 0.816 0.785 0.951 0.666
RFC 3 0.842 0.992 0.972 0.738 0.961 0.735 0.865 0.911 0.944 0.856 0.874 0.886 0.954 0.899 0.844 0.810 0.810 0.908 0.642
RFC 3* 0.908 0.997 0.939 0.825 0.947 0.764 0.880 0.905 0.920 0.886 0.825 0.911 0.975 0.911 0.926 0.788 0.798 0.929 0.706
MLP 1 0.719 0.964 0.892 0.554 0.903 0.716 0.529 0.587 0.761 0.544 0.571 0.645 0.642 0.486 0.492 0.522 0.519 0.730 0.501
MLP 1* 0.922 0.519 0.874 0.796 0.723 0.646 0.935 0.886 0.712 0.944 0.951 0.785 0.951 0.908 0.862 0.712 0.541 0.385 0.507
MLP 2 0.731 0.982 0.886 0.762 0.807 0.270 0.513 0.568 0.654 0.538 0.510 0.712 0.553 0.461 0.516 0.529 0.565 0.773 0.577
MLP 2* 0.812 0.962 0.923 0.812 0.707 0.635 0.914 0.819 0.899 0.905 0.926 0.853 0.948 0.825 0.822 0.382 0.519 0.865 0.620
MLP 3 0.455 0.835 0.918 0.719 0.907 0.719 0.440 0.486 0.770 0.605 0.581 0.712 0.498 0.688 0.513 0.470 0.553 0.782 0.489
MLP 3* 0.916 0.727 0.934 0.767 0.912 0.730 0.920 0.798 0.767 0.938 0.941 0.669 0.186 0.926 0.865 0.804 0.522 0.834 0.535
ADC 1 0.947 0.999 1.0 0.894 0.958 0.820 0.886 0.966 0.978 0.892 0.908 0.951 0.996 0.941 0.837 0.828 0.850 0.941 0.651
ADC 1* 0.982 0.997 1.0 0.916 0.960 0.835 0.978 0.978 0.993 0.975 0.978 0.963 0.993 0.978 0.917 0.868 0.896 0.957 0.746
ADC 2 0.952 1.0 1.0 0.892 0.956 0.819 0.902 0.963 0.987 0.908 0.908 0.941 0.969 0.929 0.834 0.819 0.868 0.932 0.660
ADC 2* 0.951 0.999 1.0 0.917 0.969 0.842 0.969 0.981 0.996 0.966 0.972 0.981 1.0 0.948 0.926 0.862 0.877 0.935 0.737
ADC 3 0.960 0.999 1.0 0.911 0.965 0.827 0.917 0.963 0.963 0.929 0.911 0.954 0.990 0.981 0.896 0.859 0.807 0.944 0.730
ADC 3* 0.987 1.0 1.0 0.922 0.970 0.835 0.993 0.960 0.996 0.981 0.984 0.987 0.990 0.990 0.960 0.889 0.886 0.960 0.758
GNB 1 0.853 0.885 0.865 0.620 0.886 0.722 0.675 0.850 0.822 0.694 0.697 0.850 0.905 0.847 0.746 0.584 0.608 0.889 0.599
GNB 1* 0.933 0.875 0.850 0.745 0.841 0.714 0.822 0.932 0.847 0.703 0.685 0.853 0.923 0.886 0.828 0.633 0.608 0.862 0.614
GNB 2 0.855 0.978 0.807 0.541 0.914 0.731 0.712 0.871 0.840 0.645 0.703 0.831 0.941 0.847 0.697 0.584 0.737 0.899 0.590
GNB 2* 0.862 0.854 0.856 0.703 0.814 0.704 0.752 0.847 0.853 0.752 0.721 0.840 0.883 0.862 0.782 0.571 0.629 0.840 0.550
GNB 3 0.834 0.963 0.746 0.597 0.886 0.718 0.776 0.844 0.825 0.694 0.678 0.819 0.926 0.868 0.556 0.605 0.605 0.868 0.556
GNB 3* 0.941 0.981 0.700 0.536 0.919 0.748 0.764 0.871 0.840 0.740 0.681 0.840 0.941 0.868 0.813 0.642 0.614 0.822 0.657
QDA 1 0.316 0.762 0.956 0.600 0.755 0.656 0.755 0.645 0.859 0.678 0.758 0.874 0.984 0.828 0.721 0.633 0.617 0.850 0.568
QDA 1* 0.524 0.920 0.912 0.820 0.777 0.713 0.917 0.883 0.957 0.948 0.874 0.871 0.990 0.948 0.883 0.801 0.516 0.862 0.733
QDA 2 0.765 0.930 0.884 0.514 0.721 0.573 0.850 0.840 0.840 0.691 0.740 0.862 0.966 0.810 0.688 0.623 0.764 0.874 0.556
QDA 2* 0.795 0.965 0.825 0.527 0.799 0.586 0.782 0.951 0.865 0.782 0.761 0.886 0.990 0.929 0.779 0.605 0.516 0.911 0.758
QDA 3 0.772 0.968 0.893 0.499 0.678 0.521 0.547 0.853 0.871 0.813 0.727 0.859 0.990 0.889 0.672 0.617 0.660 0.856 0.602
QDA 3* 0.949 0.967 0.998 0.443 0.851 0.563 0.935 0.905 0.911 0.935 0.975 0.920 0.981 0.929 0.730 0.681 0.529 0.828 0.672
NB 1 0.733 0.713 0.876 0.711 0.711 0.712 0.703 0.770 0.645 0.596 0.654 0.611 0.568 0.642 0.599 0.474 0.525 0.663 0.467
NB 1* 0.744 0.706 0.870 0.706 0.706 0.706 0.669 0.743 0.672 0.568 0.623 0.574 0.568 0.657 0.626 0.507 0.516 0.651 0.492
NB 2 0.733 0.719 0.810 0.728 0.726 0.729 0.678 0.755 0.642 0.584 0.629 0.593 0.565 0.617 0.587 0.474 0.522 0.654 0.495
NB 2* 0.707 0.703 0.777 0.705 0.705 0.705 0.694 0.724 0.663 0.596 0.623 0.620 0.544 0.660 0.611 0.507 0.522 0.648 0.461
NB 3 0.720 0.729 0.852 0.720 0.717 0.720 0.672 0.764 0.645 0.568 0.642 0.657 0.538 0.633 0.617 0.513 0.522 0.648 0.519
NB 3* 0.732 0.742 0.868 0.724 0.723 0.724 0.700 0.779 0.639 0.562 0.648 0.571 0.544 0.629 0.565 0.498 0.538 0.672 0.495

A01 A02 A03 A04 A05 A06 A07 A08 A09 A10 A11 A12 A13 A14 A15 A16 A17 A18 A19

old experiment results

A07, 10284 samples, 48 speakers

Model Accuracy
CART 0.9

A07, 964 samples, 5 speakers

Model Accuracy
CART 0.938
SVM 0.941
LR 0.483
KNN 0.944
GMM 0.079
LDA 0.948
SVC1 0.522
SVC2 0.948
GPC 0.944
RFC 0.944
MLP 0.483
ADC 0.944
GNB 0.944
QDA 0.944
NB 0.516

Average accuracy generated using 10 iterations classifying audio with synthetic techniques where the bit rate is discriminant.

System IDs: A07, A10, A11, A13, A14
Speakers involved (5): LA_0012, LA_0013, LA_0047, LA_0023, LA_0038

model A07 A10 A11 A13 A14
CART 0.938 0.954 0.905 0.951 0.859
SVM 0.957 0.948 0.929 0.969 0.880
LR 0.510 0.510 0.470 0.452 0.489
KNN 0.963 0.948 0.923 0.966 0.880
GMM 0.957 0.957 0.064 0.033 0.837
LDA 0.954 0.941 0.932 0.963 0.877
SVC1 0.495 0.495 0.532 0.461 0.529
SVC2 0.957 0.957 0.926 0.960 0.883
GPC 0.957 0.948 0.932 0.966 0.880
RFC 0.948 0.960 0.914 0.951 0.880
MLP 0.510 0.510 0.529 0.452 0.489
ADC 0.954 0.954 0.911 0.948 0.880
GNB 0.960 0.948 0.932 0.966 0.883
QDA 0.960 0.948 0.932 0.966 0.883
NB 0.489 0.489 0.529 0.452 0.510

Average accuracy generated using 10 iterations classifying audio with synthetic techniques where the bit rate is not discriminant.

System IDs: A08, A09, A12, A15, A16, A17, A18, A19
Speakers involved (5): LA_0012, LA_0013, LA_0047, LA_0023, LA_0038

model A08 A09 A12 A15 A16 A17 A18 A19
CART 0.792 0.770 0.767 0.856 0.724 0.532 0.547 0.535
SVM 0.856 0.840 0.813 0.902 0.755 0.470 0.571 0.495
LR 0.501 0.486 0.477 0.474 0.477 0.477 0.440 0.498
KNN 0.850 0.807 0.810 0.886 0.740 0.525 0.623 0.553
GMM 0.847 0.293 0.330 0.892 0.327 0.544 0.422 0.415
LDA 0.868 0.850 0.807 0.892 0.749 0.477 0.645 0.553
SVC1 0.501 0.519 0.535 0.544 0.532 0.477 0.452 0.501
SVC2 0.862 0.844 0.813 0.902 0.749 0.477 0.611 0.544
GPC 0.862 0.847 0.822 0.905 0.752 0.535 0.568 0.544
RFC 0.853 0.807 0.816 0.892 0.733 0.510 0.620 0.544
MLP 0.501 0.513 0.477 0.474 0.477 0.522 0.559 0.498
ADC 0.837 0.822 0.816 0.902 0.749 0.535 0.605 0.550
GNB 0.865 0.847 0.795 0.899 0.749 0.477 0.602 0.559
QDA 0.865 0.847 0.795 0.899 0.749 0.477 0.602 0.559
NB 0.498 0.513 0.522 0.525 0.522 0.477 0.440 0.498

Average accuracy generated using 10 iterations classifying audio with synthetic techniques where the bit rate is not discriminant. (part 2)

System IDs: A01, A02, A03, A04, A05, A06
Speakers involved (7): LA_0069, LA_0070, LA_0071, LA_0072, LA_0073, LA_0074, LA_0075

model A01 A02 A03 A04 A05 A06
CART 0.872 0.585 0.628 0.755 0.611 0.645
SVM 0.919 0.542 0.499 0.833 0.510 0.466
LR 0.711 0.711 0.692 0.713 0.711 0.711
KNN 0.915 0.683 0.694 0.820 0.691 0.718
GMM 0.084 0.489 0.700 0.172 0.493 0.342
LDA 0.917 0.711 0.726 0.833 0.711 0.714
SVC1 0.710 0.707 0.689 0.711 0.706 0.705
SVC2 0.913 0.711 0.720 0.832 0.711 0.723
GPC 0.914 0.711 0.729 0.833 0.711 0.726
RFC 0.912 0.711 0.712 0.829 0.706 0.720
MLP 0.711 0.711 0.692 0.286 0.711 0.711
ADC 0.913 0.707 0.716 0.820 0.710 0.721
GNB 0.914 0.711 0.725 0.833 0.711 0.712
QDA 0.914 0.711 0.725 0.833 0.711 0.712
NB 0.711 0.711 0.692 0.713 0.711 0.711

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