Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design

In today's music industry, album cover design is as crucial as the music itself, reflecting the artist's vision and brand. However, many AI-driven album cover services require subscriptions or technical expertise, limiting accessibility. To address these challenges, we developed Music2P, an open-source, multi-modal AI-driven tool that streamlines album cover creation, making it efficient, accessible, and cost-effective through Ngrok. Music2P automates the design process using techniques such as Bootstrapping Language Image Pre-training (BLIP), music-to-text conversion (LP-music-caps), image segmentation (LoRA), and album cover and QR code generation (ControlNet). This paper demonstrates the Music2P interface, details our application of these technologies, and outlines future improvements. Our ultimate goal is to provide a tool that empowers musicians and producers, especially those with limited resources or expertise, to create compelling album covers.

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Publication Details

Published
2024-10-20
DOI
https://doi.org/10.1145/3627673.3679223
Primary Topic
Music and Audio Processing
Type
article
Field-Weighted Citation Impact
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article

Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design

Weibo Yang, Zhi-Qi Cheng, J. Choi, Gye Woon Choi et al.
Music and Audio Processing
article

Music2P: A Multi-Modal AI-Driven Tool for Simplifying Album Cover Design

Weibo Yang, Zhi-Qi Cheng, J. Choi, Gye Woon Choi, J. Han
article en

Abstract

In today's music industry, album cover design is as crucial as the music itself, reflecting the artist's vision and brand. However, many AI-driven album cover services require subscriptions or technical expertise, limiting accessibility. To address these challenges, we developed Music2P, an open-source, multi-modal AI-driven tool that streamlines album cover creation, making it efficient, accessible, and cost-effective through Ngrok. Music2P automates the design process using techniques such as Bootstrapping Language Image Pre-training (BLIP), music-to-text conversion (LP-music-caps), image segmentation (LoRA), and album cover and QR code generation (ControlNet). This paper demonstrates the Music2P interface, details our application of these technologies, and outlines future improvements. Our ultimate goal is to provide a tool that empowers musicians and producers, especially those with limited resources or expertise, to create compelling album covers.

Handong Global University (KR), Ulsan National Institute of Science and Technology (KR), Carnegie Mellon University (US)
Openalex Percentile: Top 80%
Music and Audio Processing
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