First author | Dataset | Features | Classifiers | Best performance |
---|---|---|---|---|
Felipe [43] (2019) | iCOPE (pain vs. no pain) | Mel Scale (MS), MFCC, | SVM | 71.68% |
 |  | Constant-Q Chromagram (CQC) |  |  |
 |  | Local Binary Pattern (LBP), |  |  |
 |  | Local Phase Quantization (LPQ), |  |  |
 |  | Robust Local Binary Pattern (RLBP) |  |  |
 |  | extracted from spectrogram |  |  |
Sharma [39] (2019) | Donate A Cry (hungry, burp needed, | Mean frequency; standard deviation; | K-means clustering, | 81.27% |
 | belly pain, discomfort, tired, lonely, | median frequency; third quartile range; | hierarchical clustering, Gaussian |  |
 | feeling cold/hot, is scared, unidentified) | spectral entropy; kurtosis, skewness, | mixture models clustering |  |
 |  | spectral flatness, etc. |  |  |
Maghfira [36] (2019) | Dunstan Baby Database (pain, hunger, | Spectrogram | CNN-RNN | 94.97% |
 | discomfort, need to burp, belly pain) |  |  |  |
Franti [9] (2018) | Dunstan Baby Database (pain, hunger, | Spectrogram | CNN | 89% |
 | discomfort, need to burp, belly pain) |  |  |  |
Liu [13] (2018) | NICU recorded (draw attention cry, | LPC, LPCC, MFCC, BFCC | Nearest Neighbor | 76.4% |
 | diaper change needed cry, and hungry) |  | Artificial Neural Network |  |
Turan [41] (2018) | CRIED | Spectrogram | Capsule Network | 86.1% |
Osmani [67] (2017) | Dunstan Baby Database (hunger, | spectrum, pitch, zero-crossing rate, | SVM, Bagging Decision Tree, | N/A |
 | pain, tiredness, belly pain, need burp) | root mean square, intensity, energy along | and Boosted Trees, |  |
 |  | with their calculated statistics (mean, |  |  |
 |  | variance, skewness, etc) |  |  |
Chang [50] (2016) | Collected from National Taiwan | Spectrogram | CNN | 78.5% |
 | University Hospital (hungry, pain, and sleep) |  |  |  |
Bano [20] (2015) | Self-recorded (hungry, need to | Pitch short-time energy MFCC | KNN | 86% |
 | burp, sleepy, pain, discomfort) | Statistical properties of MFCC |  |  |
Orlandi [21] (2015) | Self-recorded (full term vs. preterm) | CU length, F0 median, F0 mean, | Logistic regression, | 87% |
 |  | F0 standard deviation, F0 minimum, | Multilayer perceptron NN, |  |
 |  | F0 maximum, number of estimated | Support Vector Machine, |  |
 |  | F0 values, F123 median, | and Random Forest |  |
 |  | F123 mean, F123 standard deviation, |  |  |
 |  | F123 minimum, F123 maximum |  |  |
Bhagatpatil [22] (2015) | Self-recorded (pain, hunger, discomfort, | LFCC, MFCC | K-mean clustering, KNN | 91.58% |
 | need to burp, belly pain) |  |  |  |
Rosales-Pérez [71] (2014) | Baby Chillanto (hungry vs. pain) | MFCC, LPC | Fuzzy model | 97.96% |
Yamamoto [23] (2013) | Self-recorded (discomfort, hungry, sleepy) | FFT | Nearest neighbor | 62.1% |