MusicTwins: Training Audio-Language Models to Listen like Their Persona

MusicTwins is a framework that trains audio‑language models to emulate individual personas by combining persona summaries, personal memory, and post‑training. It builds persona representations from human writings that capture background, views, personality, writing style, and a musical profile, and then fine‑tunes Audio Flamingo Next using supervised learning and reinforcement learning. Evaluation on ten held‑out personas shows significant gains in persona fidelity, including personality, writing style, and music‑related responses.

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• llms
• reinforcement-learning
• fine-tuning