A sound generation model is a model that generates audio according to given conditions. In the provided context, it refers specifically to a system that takes video as input and produces sound in real time while maintaining temporal synchronization with the visual content. The generated audio can include continuous sounds such as ambient noise or background sound, as well as momentary event sounds, for example the sound of a glass falling and breaking on the floor. The model achieves synchronization by incorporating temporally aligned visual features into the input.
The context mentions SpecMaskFoley1 and SpecMaskGIT3 as examples of real-time sound generation models. Rather than simply playing back pre-recorded audio, these models generate sound on the fly in response to the video. In the described production, the model was trained on paired data consisting of actual monorail window footage and ambient sounds recorded inside the vehicle. The system was then tuned to balance fidelity to the video, synchronization accuracy, and naturalness of the resulting sound.
The available context is limited to this specific work and does not provide a broader general definition of sound generation models beyond these implementation details.