Multi-Task Self-Supervised Learning for Disfluency Detection
Table 4: Ablation over the two self-supervised tasks. “Random-Initial” means training transformer network on gold disfluency detection data with random initialization.
['Method', 'Full P', 'Full R', 'Full F1', '1000 sents P', '1000 sents R', '1000 sents F1']
We explicitly compare the impact of the tagging task and the sentence classification task. Higher performance is achieved by combining the two self-supervised tasks, which demonstrates that the two tasks can coexist harmoniously, and share useful information between each other.