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Orfeu

Named after the Brasilian pronouniciation of Orfeus, the Greek God of music.

While Spotify's recommendation algorithm is powerful, it focuses on music similarity, often feeding you a playlist regurgitation of genres you already know. It doesn't take risks and it focuses on marketing music instead of educating about music. Orfeu aims to break this cycle by introducing listeners to a broader scope of genres along with their historical and cultural importance.

Demo

Example

  • Indonesia's Music Legacy: Known for blending traditional and modern influences.
  • Orfeu highlights soulful, pop ballads, and beach songs from Indonesia. (click on image)
Indonesia example

Methodology

The data was collected by scraping everynoise.com using web-scraping libraries BeautifulSoup and Scrapy. This data includes an extensive list of (>6000) genres, compared to the 126 that Spotify API provides, classified using ML into three distinct playlist types.

  • The Sound: A collection representing the general sound of the genre.
  • The Pulse: Core songs beloved by the main listener demographic.
  • The Edge: Tracks that represent the more experimental aspects of the genre.

A natural language processing model SpaCy was used to identify locations and separate playlists into geographic regions. This can be explored on subpage /locations

How to Use

Visit the Orfeu website to discover a new genre each day. The site features:

  • A randomly selected genre.
  • A link to a Spotify playlist curated to explore the genre.
  • Key descriptive points about the genre, web scraped from Wikipedia.

I encourage users to listen to a few songs from different artists within the genre and perform a simple Google search to learn more about its cultural context.

Future Work

plan to add features:

  • Lists of the most popular artists and songs within each genre.
  • Insights into the genre’s influence on others.
  • Detailed explanations of the rhythms, instruments, and cultural ties that define the genre.

Tools

  • Web Scraping: BeautifulSoup, Scrapy
  • Data Cleaning: Python (pandas, numpy)
  • Visualizations: D3.js
  • Music Data: Spotify API, LastFM API, MusixMatch API
  • Geographical Data: Google Maps API