Natural Language Playlist

The tool excels at understanding musical and cultural features like genre, lyrical meaning, sonics, and vibes. It supports login with Spotify to generate playlists directly on the user's account, or users can continue as a guest. The model responds best to clear, positive language, and can handle obscure genres and hyper-specific lyrical themes. Users can describe playlists using adjectives and multiple sentences to get more accurate results.

Natural Language Playlist is ideal for discovering new music based on specific moods, genres, or themes. For example, users can create playlists like "Midwest Emo songs to cry in the shower to because my girlfriend broke up with me" or "Very danceable, positive mood, fast tempo, high energy, songs for lovers." It is also useful for exploring obscure genres and hyper-specific lyrical themes that traditional search might not capture.

The tool was created by Abelardo Riojas, a 23-year-old Data Science graduate student and music enthusiast. He curated a dataset of textual song metadata to build the tool, which explores the relationship between language, music, and culture. The project is aimed at music lovers, and the creator shares updates on Instagram and is open to business inquiries via email or LinkedIn. Independent music artists can also feature their songs on the platform.