RESEARCH
The development process began with studying how real DJs manage live sets, especially how they build momentum and interact with the crowd. I analyzed the tone, pacing, and timing of professional MCs across club and radio performances. Technical research included testing multiple AI models for text generation and speech synthesis, comparing tools like OpenAI’s GPT models and ElevenLabs for realistic voice output. Additionally, I explored user behavior to ensure features like track-based cues, crowd-energy control, and speech frequency felt intuitive and adaptable to different event environments.
DESIGN
The interface was built for simplicity and performance, resembling professional DJ decks with waveform visuals, dual-track playback, and dynamic meters. Every feature—like start, pause, skip, and MC mode selection—was designed for immediate accessibility. The MC controls allow users to toggle between modes (Off, Manual, Track-based, Interval, and Smart) while adjusting energy and tone. Visual cues such as audio wave animations and track timers enhance usability. The YouTube integration and local library management were designed to make importing and organizing music effortless for any user.
DEVELOPMENT