Research Article
Transformer based Neural Joke Generator
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 183 - Issue 34 |
| Published: Oct 2021 |
| Authors: Taaha Kazi, Sameer Joshi, Steeve Kaitharath, Imran Ali Mirza |
10.5120/ijca2021921724
|
Taaha Kazi, Sameer Joshi, Steeve Kaitharath, Imran Ali Mirza . Transformer based Neural Joke Generator. International Journal of Computer Applications. 183, 34 (Oct 2021), 1-4. DOI=10.5120/ijca2021921724
@article{ 10.5120/ijca2021921724,
author = { Taaha Kazi,Sameer Joshi,Steeve Kaitharath,Imran Ali Mirza },
title = { Transformer based Neural Joke Generator },
journal = { International Journal of Computer Applications },
year = { 2021 },
volume = { 183 },
number = { 34 },
pages = { 1-4 },
doi = { 10.5120/ijca2021921724 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2021
%A Taaha Kazi
%A Sameer Joshi
%A Steeve Kaitharath
%A Imran Ali Mirza
%T Transformer based Neural Joke Generator%T
%J International Journal of Computer Applications
%V 183
%N 34
%P 1-4
%R 10.5120/ijca2021921724
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Humor is a complex and intrinsic part of human conversation, which involves a deep understanding of grammatical structure and knowledge of the world. Building computational models that can identify and generate humor remains a challenging field. This work presents a neural network based joke generator that employs a transformer-based architecture. To improve the generator's performance, the model was further trained with Proximal Policy Optimization (PPO), a reinforcement learning algorithm. The model's performance was evaluated by human ratings by conductingqualitative analysis.
References
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