A real-time sound generation model is a sound synthesis model that takes video as input and generates matching audio on the fly while maintaining temporal synchronization with the visual content. In the provided context, models based on SpecMaskFoley1 and SpecMaskGIT fall into this category. They incorporate video features, or temporal synchronization features derived from video, so that the generated sound aligns with what is happening on screen.
A key characteristic of this model type is that it can produce not only continuous sounds such as ambient noise or background audio, but also momentary sounds tied to specific events, such as a glass falling to the floor and breaking, at the synchronized moment in the video. Rather than playing back precomposed audio in loop with the image, the system generates sound each time according to the current visual input. This makes the sound-generation process itself part of the viewing experience.
In the described project, the model was trained using paired data consisting of real monorail window footage and ambient sounds recorded inside the train. Early outputs were refined based on feedback that emphasized avoiding unnatural electronic or reverse-like textures and instead capturing a natural sense of speed and motion. The context does not provide a broader technical definition beyond this project-specific use, so the term should be understood here in that limited sense.