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Image to Modern Chinese Poetry Creation via a Constrained Topic-aware Model
ACM Transactions on Multimedia Computing, Communications, and Applications ( IF 5.2 ) Pub Date : 2020-05-25 , DOI: 10.1145/3381858 Lingxiang Wu 1 , Min Xu 1 , Shengsheng Qian 2 , Jianwei Cui 3
ACM Transactions on Multimedia Computing, Communications, and Applications ( IF 5.2 ) Pub Date : 2020-05-25 , DOI: 10.1145/3381858 Lingxiang Wu 1 , Min Xu 1 , Shengsheng Qian 2 , Jianwei Cui 3
Affiliation
Artificial creativity has attracted increasing research attention in the field of multimedia and artificial intelligence. Despite the promising work on poetry/painting/music generation, creating modern Chinese poetry from images, which can significantly enrich the functionality of photo-sharing platforms, has rarely been explored. Moreover, existing generation models cannot tackle three challenges in this task: (1) Maintaining semantic consistency between images and poems; (2) preventing topic drift in the generation; (3) avoidance of certain words appearing frequently. These three points are even common challenges in other sequence generation tasks. In this article, we propose a Constrained Topic-aware Model (CTAM) to create modern Chinese poetries from images regarding the challenges above. Without image-poetry paired dataset, we construct a visual semantic vector to embed visual contents via image captions. For the topic-drift problem, we propose a topic-aware poetry generation model. Additionally, we design an Anti-frequency Decoding (AFD) scheme to constrain high-frequency characters in the generation. Experimental results show that our model achieves promising performance and is effective in poetry’s readability and semantic consistency.
更新日期：2020-05-25
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