Flexible and Creative Chinese Poetry Generation Using Neural Memory

It has been shown that Chinese poems can be successfully generated by sequence-to-sequence neural models, particularly with the attention mechanism. A potential problem of this approach, however, is that neural models can only learn abstract rules, while poem generation is a highly creative process that involves not only rules but also innovations for which pure statistical models are not appropriate in principle. This work proposes a memory-augmented neural model for Chinese poem generation, where the neural model and the augmented memory work together to balance the requirements of linguistic accordance and aesthetic innovation, leading to innovative generations that are still rule-compliant. In addition, it is found that the memory mechanism provides interesting flexibility that can be used to generate poems with different styles

Bajki robotów : przegląd wybranych projektów generujących sztuczną literaturę

Artykuł zawiera przegląd wybranych projektów sztucznej twórczości w dziedzinie literatury. Zdefiniowana została sztuczna twórczość oraz aspekty prawne w zakresie prawa autorskiego i praw pokrewnych

Bajki robotów. Przegląd wybranych projektów generujących sztuczną literaturę

The article provides an overview of selected projects of artificial creations in the field of literature. We defined the concept of artificial creation and legal aspects of copyright and related rights.Artykuł zawiera przegląd wybranych projektów sztucznej twórczości w dziedzinie literatury. Zdefiniowana została sztuczna twórczość oraz aspekty prawne w zakresie prawa autorskiego i praw pokrew­nych

How Images Inspire Poems: Generating Classical Chinese Poetry from Images with Memory Networks

With the recent advances of neural models and natural language processing, automatic generation of classical Chinese poetry has drawn significant attention due to its artistic and cultural value. Previous works mainly focus on generating poetry given keywords or other text information, while visual inspirations for poetry have been rarely explored. Generating poetry from images is much more challenging than generating poetry from text, since images contain very rich visual information which cannot be described completely using several keywords, and a good poem should convey the image accurately. In this paper, we propose a memory based neural model which exploits images to generate poems. Specifically, an Encoder-Decoder model with a topic memory network is proposed to generate classical Chinese poetry from images. To the best of our knowledge, this is the first work attempting to generate classical Chinese poetry from images with neural networks. A comprehensive experimental investigation with both human evaluation and quantitative analysis demonstrates that the proposed model can generate poems which convey images accurately.Comment: Accepted by AAAI 201