9-audioClass.R

# Build model
model <- keras_model_sequential() %>% 
        layer_conv_2d(input_shape = dim(train$X)[2:4], 
                      filters = 16, kernel_size = c(3, 3),
                      activation = "relu") %>% 
        layer_max_pooling_2d(pool_size = c(2, 2)) %>% 
        layer_dropout(rate = .2) %>% 
        
        layer_conv_2d(filters = 32, kernel_size = c(3, 3),
                      activation = "relu") %>% 
        layer_max_pooling_2d(pool_size = c(2, 2)) %>% 
        layer_dropout(rate = .2) %>% 
        
        layer_conv_2d(filters = 64, kernel_size = c(3, 3),
                      activation = "relu") %>% 
        layer_max_pooling_2d(pool_size = c(2, 2)) %>%
        layer_dropout(rate = .2) %>% 
        
        layer_conv_2d(filters = 128, kernel_size = c(3, 3),
                      activation = "relu") %>% 
        layer_max_pooling_2d(pool_size = c(28, 2)) %>%
        layer_dropout(rate = .2) %>%
        
        layer_flatten() %>% 
        
        layer_dense(units = 128, activation = "relu") %>% 
        layer_dropout(rate = .5) %>% 
        layer_dense(units = ncol(train$Y), activation = "softmax")