zsxkib / mmaudio-t4

Cost-optimized MMAudio V2 (T4 GPU): Add sound to video using this version running on T4 hardware for lower cost. Synthesizes high-quality audio from video content.

  • Public
  • 75 runs
  • GitHub
  • Weights
  • Paper
  • License
Run with an API
Playground API Examples README Versions

Examples

View more

Run time and cost

This model runs on Nvidia T4 GPU hardware. We don't yet have enough runs of this model to provide performance information.

Readme

MMAudio Video-to-Audio Synthesis Model 🎵 (T4 GPU Version)

A powerful video-to-audio synthesis model (based on MMAudio V2, running on T4 GPUs for cost savings) that transforms visual content into rich, contextually appropriate audio. This model specializes in generating high-quality audio that matches the visual elements, actions, and environments in source videos while maintaining temporal consistency.

Implementation ✨

This Replicate deployment uses the MMAudio V2 model on T4 GPUs to provide advanced capabilities for video-to-audio synthesis, focusing on: - Hardware: Runs on Nvidia T4 GPUs for a lower cost per inference compared to the standard L40S version, though inference times may be longer. - High-fidelity audio generation matching visual content - Real-time synchronization with video events - Environmental sound synthesis - Action-to-sound mapping

Model Description 🎧

The model employs the sophisticated deep learning architecture of MMAudio V2, designed specifically for video-to-audio synthesis. Using advanced neural networks and temporal analysis, it processes visual information to generate corresponding audio that naturally fits the content. (This section remains the same as the model itself hasn’t changed).

Key features:

🎵 High-quality audio synthesis from video 🎭 Context-aware sound generation ⏱️ Precise temporal synchronization 🌍 Rich environmental audio synthesis 🎯 Accurate action-sound mapping 🔄 Works with diverse video sources

Predictions Examples 🌟

The model excels at transformations like: - Converting silent films to audio-enhanced versions - Adding environmental sounds to nature videos - Generating appropriate sound effects for action sequences - Creating ambient audio for different settings - Synthesizing speech-like sounds for speaking figures

Limitations ⚠️

  • Performance: Inference times may be longer compared to versions running on higher-end GPUs like the L40S.
  • Processing time increases with video length
  • Complex acoustic environments may require additional processing
  • Output quality depends on input video clarity
  • Some unique sound effects may need specialized handling
  • Resource requirements scale with video complexity
  • Performance varies with rapid scene changes

Applications 🎯

MMAudio provides valuable solutions for: - Film and video post-production - Silent film restoration - Educational content enhancement - Gaming and VR sound design - Accessibility improvements - Content creation and editing

Ethical Considerations 📝

Important points to consider: - Respect original content rights - Maintain transparency about AI-generated audio - Consider potential misuse implications - Provide appropriate attribution - Follow content creation guidelines

Star the repo on GitHub! ⭐

Follow me on Twitter/X