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Table 3 Classification of asphyxia cry from other cries

From: A review of infant cry analysis and classification

Literature

Dataset

Features

Classifiers

Performance

Ji [15] (2019)

Baby Chillanto

MFCC with Weighted Prosodic

FFNN

96.74%

Badreldine [31] (2018)

Baby Chillanto

DWT-MFCC

RBR Kernel SVM

97.7%

Zabidi [60] (2017)

Baby Chillanto database with database

MFCC Image

CNN

92.8%

 

from University of Milano-Bicocca

   

Onu [29] (2017)

Baby Chillanto

MFCC

SVM

85%

Sachin [30] (2017)

Baby Chillanto

Waveforms

AlexNet

92%

Moharir [28] (2017)

Baby Chillanto

Waveforms

GoogleNet,AlexNet

94%

Rosales-Péreza [71] (2014)

Baby Chillanto

MFCC, LPC

Fuzzy Model

90.68%

Saraswathy [33] (2012)

Baby Chillanto

Wavelet Packet Transform

PNN, GRNN

99.04%

Hariharan [86] (2012)

Baby Chillanto

STFT

PNN, GRNN, TDNN, MLP

99%

Hariharan [34] (2012)

Baby Chillanto

Weighted LPCC

PNN

99%

Sahak [91] (2010)

Baby Chilllanto asphyxia and

MFCC

SVM

95.86%

 

self-recorded normal cries

   

Sahak [92] (2010)

Database from University

MFCC

Orthogonal least square (OLS)-based SVM

93.16%

 

of Milano Bicocca

   

Zabidi [93] (2010)

Baby Chillanto

MFCC

MLP

93.38%