Year: 2017
Type: conference-paper
Abstract: Hafez is an automatic poetry generation system that integrates a Recurrent Neural Network (RNN) with a Finite State Acceptor (FSA).It generates sonnets given arbitrary topics.Furthermore, Hafez enables users to revise and polish generated poems by adjusting various style configurations.Experiments demonstrate that such "polish" mechanisms consider the user's intention and lead to a better poem.For evaluation, we build a web interface where users can rate the quality of each poem from 1 to 5 stars.We also speed up the whole system by a factor of 10, via vocabulary pruning and GPU computation, so that adequate feedback can be collected at a fast pace.Based on such feedback, the system learns to adjust its parameters to improve poetry quality.
DOI: 10.18653/v1/p17-4008
Institution: University of Southern California
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2741986794