LongMergent: Pioneering audio mixing strategies for exquisite music generation

Artificial intelligence-empowered music processing is a domain that involves the use of artificial intelligence technologies to enhance music analysis, understanding, and generation. This field encompasses a variety of tasks from music generation to music comprehension. In practical applications, the complexity of interwoven tasks, differences in data representation, scattered distribution of tool resources, and the threshold of professional music knowledge often become barriers that hinder developers from smoothly carrying out generative tasks. Therefore, it is essential to establish a system that can automatically analyze their needs and invoke appropriate tools to simplify the music processing workflow. Inspired by the recent success of Large Language Models (LLMs) in task automation, we have developed a system named LongMergent, which integrates numerous music-related tools and autonomous workflows to address user requirements. By granting users the freedom to effortlessly combine tools, this system provides a seamless and rich musical experience.

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Publication Details

Journal
Computer Software and Media Applications
Published
2025-03-26
DOI
https://doi.org/10.24294/csma11516
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

LongMergent: Pioneering audio mixing strategies for exquisite music generation

Zheng He, Lin Hong, Chang Xu, Xuan Liu et al.
Computer Software and Media Applications
Music Technology and Sound Studies
article

LongMergent: Pioneering audio mixing strategies for exquisite music generation

Zheng He, Lin Hong, Chang Xu, Xuan Liu, Zheng Liu, Kai Yang, Chaomurilige Chaomurilige
article en

Abstract

Artificial intelligence-empowered music processing is a domain that involves the use of artificial intelligence technologies to enhance music analysis, understanding, and generation. This field encompasses a variety of tasks from music generation to music comprehension. In practical applications, the complexity of interwoven tasks, differences in data representation, scattered distribution of tool resources, and the threshold of professional music knowledge often become barriers that hinder developers from smoothly carrying out generative tasks. Therefore, it is essential to establish a system that can automatically analyze their needs and invoke appropriate tools to simplify the music processing workflow. Inspired by the recent success of Large Language Models (LLMs) in task automation, we have developed a system named LongMergent, which integrates numerous music-related tools and autonomous workflows to address user requirements. By granting users the freedom to effortlessly combine tools, this system provides a seamless and rich musical experience.

Computer Software and Media ApplicationsVol. 8(1)
Minzu University of China (CN)
Openalex Percentile: Top 96%
Music Technology and Sound Studies
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