MSMO: Multimodal Summarization with Multimodal Output | |
Zhu, Junnan; Li, Haoran; Liu, Tianshang; Zhou, Yu; Zhang, Jiajun; Zong, Chengqing | |
2018 | |
会议日期 | 2018-11 |
会议地点 | Brussels, Belgium |
英文摘要 | Multimodal summarization has drawn much attention due to the rapid growth of multimedia data. The output of the current multimodal summarization systems is usually represented in texts. However, we have found through experiments that multimodal output can significantly improve user satisfaction for informativeness of summaries. In this paper, we propose a novel task, multimodal summarization with multimodal output (MSMO). To handle this task, we first collect a large-scale dataset for MSMO research. We then propose a multimodal attention model to jointly generate text and select the most relevant image from the multimodal input. Finally, to evaluate multimodal outputs, we construct a novel multimodal automatic evaluation (MMAE) method which considers both intramodality salience and intermodality relevance. The experimental results show the effectiveness of MMAE. |
内容类型 | 会议论文 |
源URL | [http://ir.ia.ac.cn/handle/173211/23200] |
专题 | 自动化研究所_模式识别国家重点实验室_自然语言处理团队 |
作者单位 | 中国科学院自动化研究所 |
推荐引用方式 GB/T 7714 | Zhu, Junnan,Li, Haoran,Liu, Tianshang,et al. MSMO: Multimodal Summarization with Multimodal Output[C]. 见:. Brussels, Belgium. 2018-11. |
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