Deep Poetry: A Chinese Classical Poetry Generation System
Yusen Liu, Dayiheng Liu, Jiancheng Lv

TL;DR
Deep Poetry is a neural network-based Chinese classical poetry generation system that accepts multi-modal inputs and allows user participation, deployed on a mobile platform for accessible creative writing.
Contribution
It introduces a neural network approach for Chinese poetry generation that supports multi-modal inputs and user interaction, unlike previous template-based systems.
Findings
Trained on over 200,000 poems and 3 million prose texts.
Supports text, images, and concepts as input modalities.
Deployed as a WeChat applet for mobile accessibility.
Abstract
In this work, we demonstrate a Chinese classical poetry generation system called Deep Poetry. Existing systems for Chinese classical poetry generation are mostly template-based and very few of them can accept multi-modal input. Unlike previous systems, Deep Poetry uses neural networks that are trained on over 200 thousand poems and 3 million ancient Chinese prose. Our system can accept plain text, images or artistic conceptions as inputs to generate Chinese classical poetry. More importantly, users are allowed to participate in the process of writing poetry by our system. For the user's convenience, we deploy the system at the WeChat applet platform, users can use the system on the mobile device whenever and wherever possible. The demo video of this paper is available at https://youtu.be/jD1R_u9TA3M.
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Taxonomy
TopicsMultimodal Machine Learning Applications · Video Analysis and Summarization · Topic Modeling
