Unsupervised Online Multitask Learning of Behavioral Sentence Embeddings
TABLE II: Behavior Identification Accuracy (%) using Multitask Sentence Embeddings
['Method', 'Embedding Model', 'Acceptance', 'Blame', 'Negativity', 'Positivity', 'Sadness', 'Humor', 'Mean Accuracy']
The addition of the multitask objective improved the classification accuracy of unsupervised sentence embeddings from the conversation model across all behaviors except Positivity in unsupervised classification with k-Means. Under supervised learning using k-NN, our multitask embeddings improved accuracy on all behaviors except Humor. In terms of mean accuracy, our multitask embeddings performed better than other sentence embeddings with an absolute improvement over no multitasking of 1.07% and 3.24% for unsupervised and supervised methods respectively. Our multitask embeddings also achieved the highest mean accuracy over all the sentence embeddings tested.