research-article

TPoet: Topic-Enhanced Chinese Poetry Generation

Authors:

Junpeng LiAuthors Info & Claims

ACM Transactions on Asian and Low-Resource Language Information Processing, Volume 22, Issue 6

Article No.: 171, Pages 1 - 15

https://doi.org/10.1145/3593805

Published: 19 June 2023 Publication History

Abstract

Chinese poetry generation has been a challenging part of natural language processing due to the unique literariness and aesthetics of poetry. In most cases, the content of poetry is topic related. In other words, specific thoughts or emotions are usually expressed regarding given topics. However, topic information is rarely taken into consideration in current studies about poetry generation models. In this article, we propose a topic-enhanced Chinese poetry generation model called TPoet in which the topic model is integrated into the Transformer-based auto-regressive text generation model. By feeding topic information to the input layer and heterogeneous attention mechanism, TPoet can implicitly learn the latent information of topic distribution. In addition, by setting multiple identifiers such as segment, rhyme, and tone, the model can explicitly learn the constraints of generated poems. Extensive experimental results show that the quality of TPoet-generated poems outperforms the current advanced models or systems, and the topic consistency and diversity in generated poems have been significantly improved as well.

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Cited By

Cao DCheng C(2024)Survey on Deep Learning Applications in Automated Chinese Poetry Composition2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE)10.1109/ICAICE63571.2024.10864023(662-666)Online publication date: 8-Nov-2024
https://doi.org/10.1109/ICAICE63571.2024.10864023

Index Terms

TPoet: Topic-Enhanced Chinese Poetry Generation
1. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Natural language generation

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Published In

cover image ACM Transactions on Asian and Low-Resource Language Information Processing

ACM Transactions on Asian and Low-Resource Language Information Processing Volume 22, Issue 6

June 2023

635 pages

ISSN:2375-4699

EISSN:2375-4702

DOI:10.1145/3604597

Editor:
Imed Zitouni
Google, USA

Issue’s Table of Contents

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 19 June 2023

Online AM: 21 April 2023

Accepted: 02 April 2023

Revised: 20 January 2023

Received: 26 July 2022

Published in TALLIP Volume 22, Issue 6

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National Natural Science Foundation of China
Major Science and Technology Projects of Yunnan Province
Inner Mongolia Science Foundation

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Cited By

Cao DCheng C(2024)Survey on Deep Learning Applications in Automated Chinese Poetry Composition2024 5th International Conference on Artificial Intelligence and Computer Engineering (ICAICE)10.1109/ICAICE63571.2024.10864023(662-666)Online publication date: 8-Nov-2024
https://doi.org/10.1109/ICAICE63571.2024.10864023

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