Table 3.

A concise comparison between all the reviewed deep learning methods sorted by year and the databases used. A black dot (•) in a cell means the corresponding database was used in the research mentioned at the bottom of the column.

Databases
EMO-DB	•	•				•			•	•	•		•					•	•		•			•
DES	•		•
eNTERFACE			•								•		•								•		•
ABC			•
SUSAS			•
SAL			•
SmartKom			•
AVEC			•		•
VAM			•		•
SEMAINE				•
SPD					•
IEMOCAP							•				•			•	•	•	•	•		•		•		•
RECOLA								•
TEDLIUM2									•
RML													•
BAUM-1s												•
AIBO											•				•						•
LDC											•				•						•
RAVDESS												•													•
Feel-25K																				•
CASIA																							•
GEMEP																							•
CREMA-D																									•
SAVEE																									•
TESS																									•
Year	2005	2010	2011	2013	2014			2016	2017			2018						2019						2020
Research	HMM, SVM [6]	SVM [17]	GerDA, RBM [22]	LSTM, BLSTM [28]	CRF, CRBM [24]	SVM, PCA, LPP, TSL [90]	DNN, ANN, ELM [23]	DCNN, LSTM [29]	CNN [21]	DCNN [26]	LSTM, MTL [33]	ANN, PSOF [19]	DCNN, DTPM, TSL [25]	LSTM, VAE [31]	GAN [86]	GAN, SVM [88]	LSTM, ATTN [94]	DCNN, LSTM [30]	CNN, VAE, DAE, AAE, AVB [32]	DCNN, GAN [89]	LDA, TSL, TLSL [91]	CNN, BLSTM, ATTN, MTL [95]	LSTM, ATTN [83]	DNN, Generative [76]	DCNN [79]