Resources
Echo Nest Client Libraries
Remix is an open source Python library for remixing audio.
Remix is a sophisticated tool to allow you to quickly, expressively, and intuitively chop up existing audio content and create new content based on the old.
It allows you to reach inside the music, and let the music's own musical qualities be your
— or your computer's —
guide in finding something new in the old.
By using Remix's knowledge of a given song's structure, you can render the familiar strange, or the strange slightly more familiar-sounding.
You can create countless parameterized variations of a given song
— or one of near-limitless length —
that respect or desecrate the original, or land on any of countless steps in between.
There's an excellent
remix tutorial written by Adam Lindsay, as well as
examples and
API documentation.
Pyechonest is an open source Python library for the Echo Nest APIs.
Pyechonest gives the Python programmer full access to all of the Echo Nest methods including
artist search, news, reviews, blogs, similar artists as well as methods for retrieving detailed analysis information about an uploaded track.
There are
examples and
API documentation.
The Echo Nest Java API is an open source Java client library for the Echo Nest developer API.
This library gives the Java programmer full access to the Echo Nest developer API.
The API includes artist-level methods such as getting artist news, reviews, blogs, audio, video, links, familiarity, hotttnesss, similar artists, and so on.
The API also includes access to the track analysis API that will allow you to get a detailed musical analysis of any music track.
This analysis includes loudness, mode, key, tempo, time signature, detailed beat structure, harmonic content, and timbre information for a track.
There are
examples and
API documentation.
Third-party Client Libraries
These libraries have been developed by folks in the Echo Nest community. Please note that these are not maintained or supported by The Echo Nest.
The Echo Nest Cocoa Framework is an open source wrapper framework written in Objective-C that makes it easy for Cocoa developers (including iPhone developers!) to connect to the The Echo Nest API for music analysis. The Echo Nest Cocoa Framework was created by Kamel Makhloufi (aka
melka).
echonestp5 is an open source client library for the
Processing programming environment that makes it easy for Processing developers to to connect to the The Echo Nest API for music analysis. echonestp5 was created by Kamel Makhloufi (aka
melka). More information on melka's
echonestp5 site.
The Flash API for the Echo Nest by developer Ryan Berdeen (aka
also) supports the track methods of the Echo Nest API, giving the Flash programmer the ability to analyze and get detailed info about the track including track metadata, loudness, mode and key along with detailed information relating to the track's rhythmic, timbrel, and harmonic content.
A Ruby interface for the Echo Nest developer API created by developer
youpy.
Scissor extension that adds remix capabilities to ruby-echonest by developer
youpy.
A Ruby API for the Echo Nest by developer Gareth Andrew (aka
gingerhendrix).
Echo Nest Articles
Some articles that show how The Echo Nest APIs are being used.
Using the time shifting capabilities of the Echo Nest remix API
Intelligently shuffling beats with remix.
Some examples of how you can use the the shell that comes with the Echo Nest Java client to interact with the Echo Nest.
Using the Echo Nest remix API to mix up audio and video.
Using the Echo Nest APIS to drive a rich music browsing experience.
Doug Repetto has produced a number of beat manipulation experiments using remix.
Experiments that explore how familiarity, hotness and similarity interact.
Building a music synchronization game with the Echo Nest APIs.
Using the Echo Nest API to build an application to analyze music and generate click plots.
Some Java code that shows how to upload tracks to the Echo Nest API
Using the Echo Nest analyze API to look at the loudness of recordings for thousands of artists.
The goal is to build a 2D visualization that like one of Edward Tufte's sparklines: a quick, snapshot overview with high information density.
In addition, having an image snapshot of a song is useful for visually-minded people who often find themselves thinking of music as in spatial or pictorial terms.
In the same way that Cicero used different rooms in his home to memorize different sections of his oratories, a 2D song-picture could provide a memorable structure for interpreting and contextualizing moments in a piece of music.
Using the Echo Nest analyze API to find out which drummers are more robot than human.
