Challenge
Music discovery often depends on knowing a song’s title, lyrics, or artist — but what happens when a melody is stuck in your head with no searchable reference point? The gap between memory and identification creates friction in an otherwise seamless digital music ecosystem.
Music discovery often depends on knowing a song’s title, lyrics, or artist — but what happens when a melody is stuck in your head with no searchable reference point? The gap between memory and identification creates friction in an otherwise seamless digital music ecosystem.
Approach
Designed Earworm as a community-driven identification app that allows users to hum, describe, or record partial melodies and tap into collective recognition. The interface prioritizes simplicity and low-friction input, while the system encourages collaborative participation — turning individual frustration into shared problem-solving.
Designed Earworm as a community-driven identification app that allows users to hum, describe, or record partial melodies and tap into collective recognition. The interface prioritizes simplicity and low-friction input, while the system encourages collaborative participation — turning individual frustration into shared problem-solving.
Impact
Transforms an isolating experience into a social one, reframing music discovery as a participatory ecosystem rather than a solo search task.
Transforms an isolating experience into a social one, reframing music discovery as a participatory ecosystem rather than a solo search task.
