Research map / Multi-agent systems and games / LLM agents
FilmComposer: LLM-Driven Music Production for Silent Film Clips
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Proposes FilmComposer, an LLM-driven pipeline that turns silent film clips into professional-style music via visual processing, rhythm-controlled MusicGen, and multi-agent assessment/arrangement/mixing in Reaper, plus a 7k-clip film music dataset MusicPro-7k.
Problem
Generating high-quality, musically developed, video-aligned music for silent film clips, which current video-to-music models fail to deliver in sampling rate, musicality, and musical development.
Approach
Simulates a professional musician's workflow: rhythm spotting and visual description extraction, rhythm-conditioned MusicGen generating a main melody (converted to MIDI/ABC), then LLM agent groups that assess, arrange, and mix the melody through a DAW to output cinematic-quality audio.
Key results
- FilmComposer achieves the best KL (1.209), FAD (0.207), and 48K sampling rate among compared methods, beating CMT, Video2Music, M2UGen, VidMuse, and MusicGen.
- In a user study with 51 participants (18 experts), over 60% preferred FilmComposer on every item; overall preference was 81.1% for experts and 90.3% for non-experts.
- Ablation: adding the multi-agent module lowers FAD from 0.219 to 0.207 and raises ImageBind ranking from 0.265 to 0.318.
Measured effects reported in the paper
| What was changed | Where | Measured | Effect |
|---|---|---|---|
| Add text control (ablation) | Rhythm-Controllable MusicGen · Film clips test set | FAD: 0.319 -> 0.219 | Helped |
| Add text control (ablation) | Rhythm-Controllable MusicGen · Film clips test set | Rhythm: 2836 -> 3646 | Helped |
| Add text control (ablation) | Rhythm-Controllable MusicGen · Film clips test set | ImageBind: 0.163 -> 0.265 | Helped |
| Add rhythm control (ablation) | Rhythm-Controllable MusicGen · Film clips test set | FAD: 0.246 -> 0.219 | Helped |
| Add rhythm control (ablation) | Rhythm-Controllable MusicGen · Film clips test set | Rhythm: 2978 -> 3646 | Helped |
| Add rhythm control (ablation) | Rhythm-Controllable MusicGen · Film clips test set | ImageBind: 0.254 -> 0.265 | Helped |
| Add multi-agent system (ablation) | FilmComposer · Film clips test set | FAD: 0.219 -> 0.207 | Helped |
| Add multi-agent system (ablation) | FilmComposer · Film clips test set | Rhythm: 3646 -> 3834 | Helped |
| Add multi-agent system (ablation) | FilmComposer · Film clips test set | ImageBind: 0.265 -> 0.318 | Helped |
| Add speaking order, Role-Play, Few-Shot Prompting, and Chain of Thought (ablation) | Agent assessment · Assessment task | Response accuracy: 77% -> 92% | Helped |
| Add speaking order, Role-Play, Few-Shot Prompting, and Chain of Thought (ablation) | Agent arrangement · Arrangement task | Response accuracy: 47% -> 89% | Helped |
| Add speaking order, Role-Play, Few-Shot Prompting, and Chain of Thought (ablation) | Agent mix · Mix task | Response accuracy: 57% -> 91% | Helped |
Surprising findings
- The multi-agent arrangement stage was reported to bring the sampling rate to cinematic 48K, which the other waveform and symbolic baselines could not provide.
- Chain-of-thought prompting contributed the largest accuracy gain for the agents, lifting arrangement accuracy from 64% to 89%.
Limitations
- Instrument selection may exceed instrument pitch range, causing omitted notes.
- Long-term narrative coherence across scenes is not modeled.
- Agent response accuracy for arrangement and mix remains below perfect in the reported setup.
Experimental setup
Datasets: LSMDC MusicPro-7k
Benchmarks: MusicPro-7k test set
Metrics: KL FAD sampling rate ImageBind ranking chroma-based diversity multi-agent musicality score rhythm cross-correlation dynamic variation instrumentation similarity
Baselines: CMT Video2Music M2UGen VidMuse MusicGen
Builds on: MusicGen CMT AutoGen MT3
Closest papers by meaning
- Customized Condition Controllable Generation for Video Soundtrack (CVPR 2025 · similarity 0.88)
- VidMuse: A Simple Video-to-Music Generation Framework with Long-Short-Term Modeling (CVPR 2025 · similarity 0.87)
- V2Meow: Meowing to the Visual Beat via Video-to-Music Generation (AAAI 2024 · similarity 0.87)
- Compose with Me: Collaborative Music Inpainter for Symbolic Music Infilling (AAAI 2025 · similarity 0.86)
- JEN-1 Composer: A Unified Framework for High-Fidelity Multi-Track Music Generation (AAAI 2025 · similarity 0.86)
- LLark: A Multimodal Instruction-Following Language Model for Music (ICML 2024 · similarity 0.85)
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