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MusicAgent: An AI Agent for Music Understanding and Generation with Large Langua
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论文简述:在这篇论文中,作者提出了一种名为MusicAgent的AI代理系统,旨在帮助用户自动分析和满足他们在音乐处理方面的需求。这个系统集成了大量的音乐相关工具和一个自主的工作流程,以支持多种任务,包括生成任务(如音色合成)和理解任务(如音乐分类)。通过使用大型语言模型(LLM)来自动化这些任务,MusicAgent为用户提供了极大的便利和灵活性。具体来说,MusicAgent从多个来源收集工具,包括Hugging Face、GitHub和网络API等。它还利用LLM(如ChatGPT)自动组织这些工具,并将用户请求分解为多个子任务并调用相应的音乐工具。这个系统的目标是让用户摆脱AI音乐工具的复杂性,使他们能够专注于创意方面。通过允许用户轻松地组合各种工具,MusicAgent为用户提供了一种无缝且丰富的音乐体验。总之,这篇论文提出了一种强大的AI代理系统MusicAgent,旨在帮助用户在音乐处理领域实现自动化和高效需求满足。通过使用大型语言模型来支持多种任务并自动分解用户请求,MusicAgent为用户提供了极大的便利性和灵活性。 论文链接: https://arxiv.org/pdf/2310.11954
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