3 accepted papers
Diffusion models have become the primary choice in audio generation. However, their slow generation speed necessitates acceleration techniques. While current audio generation methods primarily target U-Net-based models, the Diffusion Transformer (DiT) is emerging as the trend in audio generation. As…
With the great popularity of Sora, video-based audio generation has become indispensable. While numerous video-to-audio generation models have emerged, they frequently face difficulties including semantic incompatibilities and synchronization problems, especially in situations with multiple objects.…
With the development of AI-Generated Content (AIGC), text-to-audio models are gaining widespread attention. However, it is challenging for these models to generate audio aligned with human preference due to the inherent information density of natural language and limited model understanding ability.…