The Echo Nest is a music intelligence and data platform for developers and media companies. Based in Somerville, MA, the Echo Nest was a research spin-off from the MIT Media Lab to understand the audio and textual content of recorded music. Its creators intended it to perform music identification, recommendation, playlist creation, audio fingerprinting, and analysis for consumers and developers.
On March 6, 2014 Spotify announced that they had acquired The Echo Nest.
Video The Echo Nest
History
The Echo Nest was founded in 2005 from the dissertation work of Tristan Jehan and Brian Whitman at the MIT Media Lab.
In October 2010, The Echo Nest received a $7 million venture financing from Matrix Partners and Commonwealth Capital Ventures.
In July 2012 The Echo Nest received a $17.3 million Series D venture financing from Norwest Venture Partners, Matrix Partners, Commonwealth Capital Ventures and Jim Pallotta.
In March 2014, The Echo Nest was acquired by Spotify for 49.7 million euro, consisting cash and Spotify's equity.
Maps The Echo Nest
Products
The Echo Nest's product line was based on their automatically-derived database of data about 30 million songs aggregated from web crawling, data mining, and digital signal processing techniques. The company also made its data available to developers via an API used by over 7,000 developers to build independent music applications. The API was shut down on May 31, 2016 and developers were encouraged to use the Spotify API instead.
The Echo Nest released data on 1 million songs for research purposes. The company was a co-organizer of Music Hack Day.
In June 2011, the company released Echoprint, an open source and open data acoustic fingerprinting library.
Clients
The data powered music solutions for customers such as MTV, Island Def Jam, BBC, MOG, Warner Music Group, eMusic, Spotify, Rdio, Clear Channel, VEVO, Nokia and Thumbplay.
Spotify
The Echo Nest was acquired on March 6, 2014 by music streaming service Spotify. The music intelligence agency functions to help Spotify curate personalized music recommendations that are driven by algorithms. The Echo Nest is the driving force behind the playlists professionally curated on Spotify. To generate individualized Discover Weekly playlists as well as recommend suggestions in the 'Discover' section of Spotify's home page, individualized for every subscriber, the Echo Nest collects data on a user's listening habits and uses it to predict what music they will enjoy the most.
The Echo Nest has created Taste Profiles based on the listening patterns they notice about a user. Taste Profiles are an amalgamation of taste clusters of genres and subgenres. Taste Profiles and clusters are not publicly available for individual users to access but have been released to journalists and researchers.
One Echo Nest employee has created a categorical perception spectrum of genres and subgenres based on "an algorithmically-generated, readability-adjusted scatter-plot of the musical genre-space, based on data tracked and analyzed for 1461 genres by Spotify" called Every Noise At Once.
The Echo Nest has also created an internal tool for Spotify and Echo Nest employees called The Truffle Pig, which is Spotify curates mood and occasion specific playlists. The Truffle Pig is a sonically advanced search engine that can be asked to search for songs based on adjectives or feelings. The search can also be redacted for particular qualities to produce higher levels of specificity. Playlists curated by Spotify are available for public access. They are created in part by the algorithms associated with The Truffle Pig and in part by the music experts employed by Spotify. To create these playlists, one of Spotify's thirty-two resident music experts will use the Truffle Pig search engine to find songs associated with a quality or theme. From the search results, the employee can hand pick songs perfect for any playlist. These playlists include "Your Favorite Coffeehouse" and "TGIF".
See also
- Gracenote
- Pandora
- Spotify
References
External links
- The Echo Nest's website
Source of article : Wikipedia
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