Topic-Aware Pointer-Generator Networks forSummarizing Spoken Conversations
Table 1: Evaluation results of baselines and the proposed model.
['[BOLD] Model', '[BOLD] ROUGE-1  [BOLD] F1', '[BOLD] ROUGE-1  [BOLD] Precision', '[BOLD] ROUGE-1  [BOLD] Recall', '[BOLD] ROUGE-2  [BOLD] F1', '[BOLD] ROUGE-2  [BOLD] Precision', '[BOLD] ROUGE-2  [BOLD] Recall', '[BOLD] ROUGE-L  [BOLD] F1', '[BOLD] ROUGE-L  [BOLD] Precision', '[BOLD] ROUGE-L  [BOLD] Recall']
5.2.1 Evaluation I: Between the two baselines, the pointer-generator model obtains higher performance than attentive seq2seq model. Moreover, with topic-aware attentive modeling, both baseline models obtain significant improvement, and the proposed PG-Net+TA achieves the best performance.