Convolutional RNN: an Enhanced Model for Extracting Features from Sequential Data
TABLE I: Results on emotion classification task (best results in bold)
['[EMPTY]', 'Test set UA Recall [%] 2 labels', 'Test set UA Recall [%] 5 labels']
The selected model used on the test set is the one with best misclassification rate on the validation set, and training was stopped after 12 epochs of training without improvement of the misclassification rate of the validation set. Since the number of utterances from each class may vary, we report the Unweighted Average (UA) Recall, which is the official benchmark measure on this task. The UA Recall is defined to be 1nn∑i=1ri, where n is the number of classes, and the recall ri is the number of correctly classified examples from class i (true positives) divided by the total number of examples from