Table 2.

The details of layers and parameters

No.	Layers	Filter*kernel size	Unit size	Parameters	Trainable parameters	Output size
1	Dense	–	300	Relu, strides $=$ 1	9300	(N,200,300)
2	Conv1D	64*3	–	Relu, strides $=$ 1	57664	(N,198,64)
3	Conv1D	128*3	–	Relu, strides $=$ 1	24704	(N,196,128)
4	MaxPool	–	2	Strides $=$ 2	0	(N,98,128)
5	Conv1D	128*5	–	Relu, strides $=$ 1	82048	(N,94,128)
6	Conv1D	256*5	–	Relu, strides $=$ 1	164096	(N,90,256)
7	MaxPool	–	2	Strides $=$ 2	0	(N,45,256)
8	Dropout	–	–	Rate $=$ 0.5	0	(N,45,256)
9	LSTM	–	300	–	668400	(N,45,300)
10	LSTM	–	300	–	721200	(N,45,300)
11	LSTM	–	300	–	721200	(N,300)
12	Dropout	–	300	Rate $=$ 0.4	0	(N,300)
13	Dense	–	5	Softmax	1806	(N,5)