Multimodal Transformer Networks for End-to-End Video-Grounded Dialogue Systems
Table 3: Evaluated on the test data, the proposed approach achieves better objective measures than the baselines and the submissions to the challenge. The best result in each metric is highlighted in bold.
['[EMPTY]', '[BOLD] BLEU1', '[BOLD] BLEU2', '[BOLD] BLEU3', '[BOLD] BLEU4', '[BOLD] METEOR', '[BOLD] ROUGE-L', '[BOLD] CIDEr']
We compared MTN models with the baseline Hori et al. The evaluation includes 4 word-overlapping-based objective measures: BLEU (1 to 4) Papineni et al. , CIDEr Vedantam et al. The results were computed based on one reference ground-truth response per test dialogue in the test set. et al. Our Large model outperforms the best previously reported models in the challenge across all the metrics. Even our Base model with smaller parameters outperforms most of the previous results, except for entry1, which we outperform in BLEU1-3 and METEOR measures. While some of the submitted models to the challenge utilized external data or ensemble techniques Alamri et al.