arXiv cs.AI· Milan Liessens Dujardin, Kevin Miao·· 12 小时前AI 评分29
MusicTwins：训练音频语言模型像其人格一样聆听
MusicTwins: Training Audio-Language Models to Listen like Their Persona
AI 导读
MusicTwins 框架通过人格摘要、个人记忆与后训练，让音频语言模型生成特定人物的个性化响应。研究基于人类写作构建包含背景、观点、性格、写作风格和音乐画像的人格表征，并用监督微调与强化学习后训练 Audio Flamingo Next。在十个留出人格上的评测显示，该模型在人格保真度（含性格、写作风格及对音乐的响应）上有明显提升。
正文 · 原文
Abstract:People differ in how they perceive music, what associations they make with it, what they like about it, and how they respond to it. Computational models intended to simulate people in environments that include music should account for these differences. Although LLMs have been shown to reproduce aspects of human behavior, whether audio-language models (ALMs) can reproduce a specific person's responses to textual and musical stimuli remains underexplored. We introduce MusicTwins, a framework that combines persona summaries, personal memory, and post-training to generate person-specific responses. We construct persona representations from human writings, capturing background, views, personality, writing style, and a musical profile, and post-train Audio Flamingo Next through supervised fine-tuning and reinforcement learning. Evaluation on ten held-out personas shows notable improvements for Audio Flamingo Next in persona fidelity, including personality, writing style, and responses to music, supporting MusicTwins as a foundation for training audio-language models to listen like their persona.
| Subjects: | Sound (cs.SD); Artificial Intelligence (cs.AI) |
| Cite as: | arXiv:2610.32495 [cs.SD] |
| (or arXiv:2610.32495v1 [cs.SD] for this version) | |
| https://doi.org/10.48550/arXiv.2610.32495 arXiv-issued DOI via DataCite (pending registration) |
Submission history
From: Milan Liessens Dujardin [view email]
[v1]
Fri, 23 Oct 2026 11:11:45 UTC (2,513 KB)
来源：arXiv cs.AI · arxiv.org