music-curation

Create mood-aware playlists by applying genre classification, BPM matching, and energy valence tracking to design a coherent listening arc. This approach aligns audio features to build smooth energy transitions for specific contexts like workouts or study sessions.

BPM matching and energy valence tracking are audio feature analysis techniques that group tracks by tempo and emotional intensity. They ensure playlist cohesion by mapping sonic characteristics to sustain a desired mood or activity level.

Build a playlist using a seed-and-recommend workflow by inputting core tracks and expanding the list with similar music. The system maps sub-genres and audio features to recommend tracks that fit the established energy and mood constraints.

Yes, genre classification and sub-genre mapping support cohesive DJ-style curation sets. By grouping related genres and applying BPM matching, the curation process maintains stylistic consistency while managing energy arcs across the session.

Mood-based music curation works for workout and study sessions by applying BPM ranges and energy constraints tailored to each context. It tracks audio features to build distinct energy arcs, matching high-intensity workouts or focused study requirements.

Design a coherent listening experience by applying arc design to sequence tracks based on energy and valence constraints. Mapping audio features like BPM and genre ensures the playlist flows naturally and maintains the intended mood progression.