CogSound - The latest sound effect model from Zhipu AI

What is CogSound?

CogSound, the latest sound effects model from Zhipu AI, adds captivating sound effects to silent videos. Based on GLM-4V video understanding capabilities, CogSound accurately identifies and understands the semantics and emotions behind a video, adding matching audio content to silent videos. It can generate more complex sound effects, such as explosions, flowing water, musical instruments, animal sounds, and vehicle noises. The model's release marks a significant advancement for Zhipu AI in video generation, particularly in enhancing the multimodal experience of videos, increasing their immersion and realism.

CogSound's main functions

• Generate sound effects that match the visuals.:CogSound can generate sound effects that match the video, providing a richer audio-visual experience.
• Supports 4K ultra-high-definition video generation:It supports generating 10-second, 4K resolution, 60-frame ultra-high-definition videos, along with corresponding sound effects.
• Adapt to different playback needs:It supports video generation at any ratio to adapt to different playback needs and generates matching sound effects for these videos.
• Multi-channel video generation:The same command/image can generate four videos at once, each with corresponding sound effects.
• Improve video generation experience:By adding sound effects, CogSound enhances the immersiveness and realism of video content, making the video generation experience more complete and vivid.
• Sound effects function public beta:CogSound's sound effects feature will soon be available for public beta testing (expected at the end of November), and users will be able to... Zhipu Qingying Experience the sound generation service provided by CogSound.

CogSound's technical features

• Unet-based latent space diffusion:
  • High-efficiency audio generationCogSound uses a latent diffusion model to transfer the audio generation process from a high-dimensional original space to a low-dimensional latent space, which helps reduce computational complexity.
  • Optimized U-Net structureAs the core framework of the diffusion model, the U-Net structure has been optimized to improve the performance of the audio synthesis process while maintaining the high quality and efficiency of the generated audio.
• Block-based temporal alignment and cross-attention:
  • Strengthen the correlation between audio and video featuresBy introducing a block-wise temporal alignment cross-attention mechanism, CogSound can optimize feature matching between long video sequences and audio features.
  • Precise audio and video mappingBy learning the relationship between frame-level video features and audio features, we can achieve accurate audio-video mapping, ensuring that every frame can find its place in the musical notes, and that every musical note can be accurately echoed in the video.
• Rotational position encoding:
  • Improve the accuracy of time series modelingCogSound integrates rotational position encoding technology to provide a unique identifier for each position in the sequence and capture the relative relationships between positions, which helps improve temporal consistency.
  • Continuity and natural transitionRotational position coding ensures the continuity and natural transitions of audio sequences, avoiding "breaks" or "misalignments" in audio generation when handling long-sequence tasks.

CogSound application scenarios

• Video content creationIt provides video content creators with a wider range of sound effects to enhance the expressiveness of their videos.
• Advertising productionAdding matching sound effects to advertising videos can enhance the appeal and memorability of the ads.
• Post-production of film and televisionIn film and television post-production, it provides corresponding sound effects support for the visuals, improving production efficiency and quality.