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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%