Breakthrough Applications for Cross-Modal Content Generation
The Lyrics-to-MV feature models the deep correlation between the semantics of lyrics and visual elements. When inputting lyrics such as 'lonely streets at night', the system determines the cool visual style through the sentiment analysis model (Valence-Arousal model), matches the related image concepts (neon lights, rainy alleys, etc.) via the CLIP model, and ultimately calls the video generation model to synthesize the rhythmically synchronized footage. The key technological breakthrough lies in the establishment of a mapping system from musical features to visual parameters, including the demonstration of the positive correlation between BPM (beats per minute) and clip tempo.
Test data from independent musicians show that the MV production time for a 3-minute song was shortened from the traditional 72 hours to 1.5 hours. The system's built-in 'mood-vision' database contains 200+ style presets, such as 'electronic music → cyberpunk' ballad → hand-painted style' and so on. Universal Music's case shows that the technology reduces the cost of single song promotion by 60%.
This answer comes from the articleOpenCreator: integrating multiple AI models to generate creative videosThe
