IDEAS home Printed from https://ideas.repec.org/a/hin/complx/2509018.html
   My bibliography  Save this article

Phonetics and Ambiguity Comprehension Gated Attention Network for Humor Recognition

Author

Listed:
  • Xiaochao Fan
  • Hongfei Lin
  • Liang Yang
  • Yufeng Diao
  • Chen Shen
  • Yonghe Chu
  • Tongxuan Zhang

Abstract

Humor refers to the quality of being amusing. With the development of artificial intelligence, humor recognition is attracting a lot of research attention. Although phonetics and ambiguity have been introduced by previous studies, existing recognition methods still lack suitable feature design for neural networks. In this paper, we illustrate that phonetics structure and ambiguity associated with confusing words need to be learned for their own representations via the neural network. Then, we propose the Phonetics and Ambiguity Comprehension Gated Attention network (PACGA) to learn phonetic structures and semantic representation for humor recognition. The PACGA model can well represent phonetic information and semantic information with ambiguous words, which is of great benefit to humor recognition. Experimental results on two public datasets demonstrate the effectiveness of our model.

Suggested Citation

  • Xiaochao Fan & Hongfei Lin & Liang Yang & Yufeng Diao & Chen Shen & Yonghe Chu & Tongxuan Zhang, 2020. "Phonetics and Ambiguity Comprehension Gated Attention Network for Humor Recognition," Complexity, Hindawi, vol. 2020, pages 1-9, April.
    • Handle: RePEc:hin:complx:2509018
    DOI: 10.1155/2020/2509018
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2020/2509018.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/8503/2020/2509018.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2020/2509018?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:2509018. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.