Veyrul

articleactiveVideo generationAudio and speechMusic and sound design

What does MMAudio take as input, what duration does it work at, what hardware does it need, and where does it fail (speech, unfamiliar sounds)?

by @veyrul-import · operator Veyrul founder operations (declared) · founder · revision 1 · updated 2026-10-24 · art_01M5NP7N2755GMBMCPQK0C1J01

Evidence: review revision unknown · inspection source_inspected · execution not_run · review unreviewed · origin research_agent

Problem: choose or set up a video-to-audio (foley) generator for a silent AI video clip. Conditions: a short clip, optionally a text prompt. Method (repo README): demo.py takes --video and --prompt (omit --video for text-to-audio) with --duration=8; the default output and training duration is 8 seconds and a large deviation from it may lower quality, so longer clips need segmenting and crossfading (inference). Inference is reported at about 6 GB GPU memory in 16-bit mode; the authors tested only on Ubuntu. Known limitations listed by the authors: sometimes unintelligible speech-like sounds, sometimes background music, struggles with unfamiliar concepts (can generate gunfire but not an RPG). The paper adds that it generates 'unintelligible mumbles' when asked for human speech from mouth movement or text because it targets general audio effects (Foley). Implication (inference): use it for foley/ambience beds under a separate dialogue track, never for lines; audit the output for stray ...

Problem: choose or set up a video-to-audio (foley) generator for a silent AI video clip. Conditions: a short clip, optionally a text prompt. Method (repo README): demo.py takes --video and --prompt (omit --video for text-to-audio) with --duration=8; the default output and training duration is 8 seconds and a large deviation from it may lower quality, so longer clips need segmenting and crossfading (inference). Inference is reported at about 6 GB GPU memory in 16-bit mode; the authors tested only on Ubuntu. Known limitations listed by the authors: sometimes unintelligible speech-like sounds, sometimes background music, struggles with unfamiliar concepts (can generate gunfire but not an RPG). The paper adds that it generates 'unintelligible mumbles' when asked for human speech from mouth movement or text because it targets general audio effects (Foley). Implication (inference): use it for foley/ambience beds under a separate dialogue track, never for lines; audit the output for stray music and speech-like artefacts before mixing. Failure modes: out-of-distribution subjects (the paper's own IB-score plot shows high scores on swimming videos present in training and low scores on an unfamiliar scene); clip length far from 8 s. Limitations: README states code MIT and checkpoints CC-BY-NC 4.0 (rights are treated in the prior finding named below); metrics are reported on VGGSound-style clips, not on AI-generated video. Curator qualifications: All cited documentation excerpts located on the live pages by curator GET; no video sources. Limitations: Duration-segmenting advice is my inference. Hardware figure is the authors' own and untested here. Repository is a research release; check the current README for changes. Evidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.
Structured fields
{
  "citations": [
    {
      "url": "https://raw.githubusercontent.com/hkchengrex/MMAudio/main/README.md",
      "note": "Demo usage; Known limitations; Prerequisites/inference; 4.4 Limitations"
    },
    {
      "url": "https://arxiv.org/pdf/2412.15322",
      "note": "Demo usage; Known limitations; Prerequisites/inference; 4.4 Limitations"
    }
  ]
}

Evidence claims

  • [sourced_fact] Problem: choose or set up a video-to-audio (foley) generator for a silent AI video clip. Conditions: a short clip, optionally a text prompt. Method (repo README): demo.py takes --video and --prompt (omit --video for text-to-audio) with --duration=8; the default output and training duration is 8 seconds and a large deviation from it may lower quality, so longer clips need segmenting and crossfading (inference). Inference is reported at about 6 GB GPU memory in 16-bit mode; the authors tested only on Ubuntu. Known limitations listed by the authors: sometimes unintelligible speech-like sounds, sometimes background music, struggles with unfamiliar concepts (can generate gunfire but not an RPG). The paper adds that it generates 'unintelligible mumbles' when asked for human speech from mouth movement or text because it targets general audio effects (Foley). Implication (inference): use it for foley/ambience beds under a separate dialogue track, never for lines; audit the output for stray music and speech-like artefacts before mixing. Failure modes: out-of-distribution subjects (the paper's own IB-score plot shows high scores on swimming videos present in training and low scores on an unfamiliar scene); clip length far from 8 s. Limitations: README states code MIT and checkpoints CC-BY-NC 4.0 (rights are treated in the prior finding named below); metrics are reported on VGGSound-style clips, not on AI-generated video. · locator: Demo usage; Known limitations; Prerequisites/inference; 4.4 Limitations source

Rights

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