“It’s more of a vibe I’m going for”: Designing Text-to-Music Generation Interfaces for Video Creators

Background music plays a crucial role in social media videos, yet finding the right music remains a challenge for video creators. These creators, often not music experts, struggle to describe their musical goals and compare options. AI text-to-music generation presents an opportunity to address these challenges by allowing users to generate music through text prompts; however, these models often require musical expertise and are difficult to control. In this paper, we explore how to incorporate music generation into video editing workflows. A formative study with video creators revealed challenges in articulating and iterating on musical preferences, as creators described music as "vibes" rather than with explicit musical vocabulary. Guided by these insights, we developed a creative assistant for music generation using editable vibe-based recommendations and structured refinement of music output. A user study showed that the assistant supports exploration, while direct prompting is more effective for precise goals. Our findings offer design recommendations for AI music tools for video creators.