@inproceedings{ff3fce1717e540e5ad0011eafa50b73d,
title = "AI Powered Multi-model Content Creation for Virtual Gallery Using Learning Machine",
abstract = "Online digital advertising is currently a crucial marketing tool. Presently, the production of marketing content, including images, copy, and music, is still carried out using traditional manual methods. The purpose of this paper is to utilize AI technology to automatically generate diverse and contextually relevant initial drafts of marketing content. Users can gain inspiration from these drafts, resulting in significant time and manpower cost savings. Users only need to input a product image, product name, and select a music style through the webpage. Subsequently, the webpage will showcase AI-generated initial drafts of product copy with various backgrounds and arrangements. Taking inspiration from a museum concept, when users hover their mouse over the displayed product, they can simply press a designated key to play the generated music. This offers users a preliminary idea of the product in terms of imagery, copy, and music - all three aspects combined.",
keywords = "AI-generation, digital advertisement, GPT-2, music",
author = "Chen, {Yen Wen} and Chiu, {Yi Wei} and Liu, {Yu Sin} and Huang, {Chih Yu} and Shen, {Yu Chun}",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 14th IEEE Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023 ; Conference date: 12-10-2023 Through 14-10-2023",
year = "2023",
doi = "10.1109/UEMCON59035.2023.10315999",
language = "???core.languages.en_GB???",
series = "2023 IEEE 14th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "704--709",
editor = "Satyajit Chakrabarti and Rajashree Paul",
booktitle = "2023 IEEE 14th Annual Ubiquitous Computing, Electronics and Mobile Communication Conference, UEMCON 2023",
}