Archive of the sounds of work.
By a consortium of six museums – Torsten Nillson, project leader
Air pump from Prussian steam locomotive: http://www.workwithsounds.eu/sound/air-pump-steam-locomotive/
Archive of the sounds of work.
By a consortium of six museums – Torsten Nillson, project leader
Air pump from Prussian steam locomotive: http://www.workwithsounds.eu/sound/air-pump-steam-locomotive/
Machine learning library for Max and Pd.
By Ali Momeni and Jamie Bullock
https://github.com/cmuartfab/ml-lib
“Sure Be Cool If You Did”- Blake Shelton
“Drunk on You”- Luke Bryan
“Chillin’ It”- Cole Swindell
“Close Your Eyes”- Parmalee
“This is How We Roll”- Florida Georgia Line
“Ready, Set, Roll”- Chase Rice
Remix By Sir Mashalot
Here’s what the track looks like in the Infinite Jukebox http://labs.echonest.com/Uploader/index.html
Local file: Max teaching examples/new-country-mashup.mp3
reddit’s view: http://www.reddit.com/r/videos/comments/2rrca5/damning_evidence_of_how_formulaic_pop_country_has/
In Ableton Live
By Thavius Beck at Dubspot
For the Echonest API track profile response.
By Jason Sundram at Running With Data
http://runningwithdata.com/post/1321504427/danceability-and-energy
Get track analysis data for your music using the Echonest API.
The track analysis includes summary information about a track including tempo, key signature, time signature mode, danceability, loudness, liveness, speechinesss, acousticness and energy along with detailed information about the song structure (sections) beat structure (bars, beats tatums) and detailed info about timbre, pitch and loudness envelope (segment).
track API documentation: http://developer.echonest.com/docs/v4/track.html
Its a two (or three) step process. Here’s an example of how to upload your track and get an audio summary, using curl from the command line in Mac OS. Note, you will need to register with Echonest to get a developer API key here: http://developer.echonest.com/raw_tutorials/register.html
Note that the path to the filename needs to be complete or relative to the working directory. Also, in this example there was no metadata identifying the title of the song. You may want to change this before uploading. Replace the API key with your key.
curl -F “api_key=TV2C30KWEJDKVIT9P” -F “filetype=mp3” -F “track=@/Users/tkzic/internetsensors/echo-nest/bowlingnight.mp3” “http://developer.echonest.com/api/v4/track/upload”
Here is the response returned:
{“response”: {“status”: {“version”: “4.2”, “code”: 0, “message”: “Success”}, “track”: {“status”: “pending”, “artist”: “Tom Zicarelli”, “title”: “”, “release”: “”, “audio_md5”: “7edc05a505c4aa4b8ff87ba40b8d7624”, “bitrate”: 128, “id”: “TRLFXWY14ACC02F24C”, “samplerate”: 44100, “md5”: “78ccac72a2b6c1aed1c8e059983ce7c7”}}}
Here’s the query to get the analysis – using the ID returned by the previous call. Replace the API key with your key.
curl “http://developer.echonest.com/api/v4/track/profile?api_key=TV2C30KYGHTUVIT9P&format=json&id=TRLFXWY14ACC02F24C&bucket=audio_summary”
Here is the response – which also contains a URL that you can use to get more detailed segment based acoustic analysis of the track.
{
“response”: { “status”: { “code”: 0, “message”: “Success”, “version”: “4.2” }, “track”: { “analyzer_version”: “3.2.2”, “artist”: “Tom Zicarelli”, “audio_md5”: “7edc05a505c4aa4b8ff87ba40b8d7624”, “audio_summary”: { “acousticness”: 0.64550727753299, “analysis_url”: “http://echonest-analysis.s3.amazonaws.com/TR/TRLFXWY14ACC02F24C/3/full.json?AWSAccessKeyId=AKIAJRDFEY23UEVW42BQ&Expires=1420763215&Signature=OLqYwvuzVmAqp1xLTi5x4CsYJuE%3D”, “danceability”: 0.5680872294350238, “duration”: 245.91673, “energy”: 0.19974462311717034, “instrumentalness”: 0.8089125726216321, “key”: 11, “liveness”: 0.10906007889455183, “loudness”: -25.331, “mode”: 1, “speechiness”: 0.03294587631927559, “tempo”: 93.689, “time_signature”: 4, “valence”: 0.43565861274829504 }, “bitrate”: 128, “id”: “TRLFXWY14ACC02F24C”, “md5”: “78ccac72a2b6c1aed1c8e059983ce7c7”, “samplerate”: 44100, “status”: “complete” } } }
Use the analysis_url returned by the previous request. Note that it expires a few minutes after the request. But you can always re-run the audio_profile request to get a new analysis_url
curl “http://echonest-analysis.s3.amazonaws.com/TR/TRLFXWY14ACC02F24C/3/full.json?AWSAccessKeyId=AKIASVIFEY23UEGE42BQ&Expires=1420763215&Signature=OLqYwvuzVmAqp1xLTi5x4CsYJuE%3D”
The analysis result is too large to display here. For more information, get the Echonest Analyze Documentation: http://developer.echonest.com/docs/v4/_static/AnalyzeDocumentation.pdf
Design living creatures with a computer.
By Austin Heintz, article by Stephanie M. Lee at SFGate
Glowing Plants (Kickstarter): https://www.kickstarter.com/projects/antonyevans/glowing-plants-natural-lighting-with-no-electricit
Spectral slider plugin for Ableton Live
By Adam Rokhsar at Utami
http://makeyourselftransparent.tumblr.com
http://youtu.be/r-ZpwGgkGFI
Distance to nearest McDonald’s.
By Stephen Von Worley at Data Pointed
http://www.datapointed.net/2009/09/distance-to-nearest-mcdonalds/
“…circular reporting or false confirmation is a situation where a piece of information appears to come from multiple independent sources, but in fact is coming from only one source”
from Wikipedia