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The future music platform

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Brian Whitman

Brian Whitman from the Echo Nest discusses the music platform and how new startups and app developers are the future of the music industry..

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The future music platform Brian Whitman @bwhitman co-Founder & CTO,The Echo Nest
No
If by “fail” you mean “become the future of the industry”, OK.
Hello! I “teach computers to listen to music”
“Fish / Cut bait I’m a often-frustrated musician & technology person
Making something from everything
Hit prediction Taste / recommendation Automated composition Classification, tagging Feature extraction (key, tempo) Search & retrieval creepy Music retrieval and “music intelligence” applications
Retrieving Music by Rhythmic Similarity 0 0.5 1 1.5 Tempo (bpm) squaredEuclideandistance 110130 120122124126128 118 116 114 112 110 bpm 112 bpm 114 bpm 116 bpm 120 bpm 122 bpm 124 bpm 126 bpm 128 bpm 130 bpm 4 · Elias Pampalk air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria 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threetimesalady eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach branden vm−bach beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms beethoven fuguedminor future lovemetender vm−brahms 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myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn lovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheair ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio manicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmonday rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola 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bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking Fig. 2. Islands of Music representing a 7x7 SOM with 77 pieces of music. The artists and full titles of which are represented by the short identifiers here, can be found on the web page or in the thesis. 5. CONCLUSION The Islands of Music have not yet reached a level which would suggest their commerci however, they demonstrate the possibility of such systems and serve well as a tool fo research. Any part of the system can be modified or replaced and the resulting effects c Fig. IV GenreGram 5. USER INTERFACES Two new graphical user interfaces for browsing and interacting with collections of audio signals have been developed (Figure IV,V) . They are based on the extracted feature vectors and the automatic genre classification results. • GenreGram is a dynamic real-time audio display for showing automatic genre classification results. Each genre is represented as a cylinder that moves up and down in real Fig. V GenreSpace 6. FUTURE WORK An obvious direction for future research is to expand the hierarchy both in width and depth. The combinati segmentation [20] with automatic genre classification provide a way to browse audio to locate regions of in Another interesting direction is the combination of the gra user interfaces described with automatic similarity retriev takes into account the automatic genre classification. In its form the beat analysis algorithm can not be performed in re Musical Genres (Classical, Country…..) the combined set described in this paper was used. For the Classical Orchestra, Piano…) only the Music Surface features were d for the Speech Genres (MaleVoice, FemaleVoice…) uency cepstral coefficients [16] (MFCC) were used. are features commonly used in speech recognition . M usic ssical C ountry D isco H ipH op Jazz R ock estra P iano C hoir StringQ uartet Computers “helping” you discover music
Columbia University, NYC MIT Media Lab finishing my dissertation Academic lifestyle
Always do it automatically, on everything
Started a company - are you sure you want to do this?
The Echo Nest 2010 Somerville, MA USA 30 people 200 computers Lots of products 5,000,000,000 documents 1,200,000 artists 20,000,000 songs Where we’ve gotten in the past few years
Good news! We’re on the right track
We are a music application development platform that knows more about music content and music consumers than anyone.
The platform
You’re a music fan. How do you get to music? Or inversely, you’re a musician. How do you get to your fans?
Only 10 years ago - pretty terrible. Buy a thing or borrow it.
5 years ago - a little better. Easier to self publish and discover.
Today.The choices for distribution are immense.
App developers are now the future of the music business.
Good news: thousands of developers working on music. Bad news: most have been locked out of the business.
Until now!
Music platform Content Engineering Audience What a music platform gives you
Music platform Content Engineering Audience Who can do what
The power of APIs
This is the Echo Nest’s business!
Similarity Acoustic analysisArtist metrics Feeds RecommendationSearch / Tags Metadata Predictive analytics Content / Streaming So many possibilities all built into the plaftorm Fingerprint
vibrant, active developer community developer API discovery playlisting mobile music games music visualizers remix apps analytics targeted marketing branded entertainment 100s of apps to date Not just independents-- the power is from partnerships
Content / Streaming Where can I get audio from?
Probably shouldn’t playYouTube videos Content / Streaming
Or stream from blogs Content / Streaming
Content / Streaming But the distributors & labels are getting there!
Content / Streaming They believe in this as much as we do.
Artist Mood Key Tempo Popularity Familiarity Location This Pandora competitor was built in 24 hours by one developer. It has 10 million songs available.
An employee built this algorithm during a MHD Within a week there were 3 competing web apps for it.
audiokicker is an upcoming iPhone app for social music
audiokicker uses Echo Nest for recommendation and 7digital for content
EN client streaming service Thumbplay
All the potential is a bit baffling. This very inspired person is building “Frasier”-themed experiences. http://music.joshmillard.com/2010/06/04/nine-inch-niles-the-seattleward-spiral/
There are hundreds of apps available on the platform already From big companies to one-person ideas
Someone in this room is going to invent the way music is experienced in the future.
The future music platform
The future music platform

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The future music platform

  • 1. The future music platform Brian Whitman @bwhitman co-Founder & CTO,The Echo Nest
  • 2.
  • 3. No
  • 4. If by “fail” you mean “become the future of the industry”, OK.
  • 5. Hello! I “teach computers to listen to music”
  • 6. “Fish / Cut bait I’m a often-frustrated musician & technology person
  • 8. Hit prediction Taste / recommendation Automated composition Classification, tagging Feature extraction (key, tempo) Search & retrieval creepy Music retrieval and “music intelligence” applications
  • 9. Retrieving Music by Rhythmic Similarity 0 0.5 1 1.5 Tempo (bpm) squaredEuclideandistance 110130 120122124126128 118 116 114 112 110 bpm 112 bpm 114 bpm 116 bpm 120 bpm 122 bpm 124 bpm 126 bpm 128 bpm 130 bpm 4 · Elias Pampalk air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond air avemaria elise kidscene mond therosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherosetherose memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady memory rainbow threetimesalady eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution eternalflame feeling revolution americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b americanpie drummerboy friend yesterday−b addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia addict ga−lie newyork sml−adia bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld lovedwoman bigworld 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pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge korn−freak limp−pollution pr−deadcell pr−revenge frozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozenfrozen dancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueendancingqueen unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart unbreak− myheart ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn ga−nospeech torn lovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheairlovsisintheair ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue ga−doedel ga−japan nma−bigblue rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot rhcp− californication sl−whatigot cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj cocojambo macarena rockdj gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio gowest radio manicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmondaymanicmonday rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world rhcp− world limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether limp− n2gether eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola supertrouper eifel65−blue fromnewyorktola 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bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bongobong themangotree bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit bfmc−uprocking bfmc−instereo bfmc−rocking bfmc−skylimit 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Islands of Music representing a 7x7 SOM with 77 pieces of music. The artists and full titles of which are represented by the short identifiers here, can be found on the web page or in the thesis. 5. CONCLUSION The Islands of Music have not yet reached a level which would suggest their commerci however, they demonstrate the possibility of such systems and serve well as a tool fo research. Any part of the system can be modified or replaced and the resulting effects c Fig. IV GenreGram 5. USER INTERFACES Two new graphical user interfaces for browsing and interacting with collections of audio signals have been developed (Figure IV,V) . They are based on the extracted feature vectors and the automatic genre classification results. • GenreGram is a dynamic real-time audio display for showing automatic genre classification results. Each genre is represented as a cylinder that moves up and down in real Fig. V GenreSpace 6. FUTURE WORK An obvious direction for future research is to expand the hierarchy both in width and depth. The combinati segmentation [20] with automatic genre classification provide a way to browse audio to locate regions of in Another interesting direction is the combination of the gra user interfaces described with automatic similarity retriev takes into account the automatic genre classification. In its form the beat analysis algorithm can not be performed in re Musical Genres (Classical, Country…..) the combined set described in this paper was used. For the Classical Orchestra, Piano…) only the Music Surface features were d for the Speech Genres (MaleVoice, FemaleVoice…) uency cepstral coefficients [16] (MFCC) were used. are features commonly used in speech recognition . M usic ssical C ountry D isco H ipH op Jazz R ock estra P iano C hoir StringQ uartet Computers “helping” you discover music
  • 10. Columbia University, NYC MIT Media Lab finishing my dissertation Academic lifestyle
  • 11. Always do it automatically, on everything
  • 12. Started a company - are you sure you want to do this?
  • 13. The Echo Nest 2010 Somerville, MA USA 30 people 200 computers Lots of products 5,000,000,000 documents 1,200,000 artists 20,000,000 songs Where we’ve gotten in the past few years
  • 14. Good news! We’re on the right track
  • 15. We are a music application development platform that knows more about music content and music consumers than anyone.
  • 17. You’re a music fan. How do you get to music? Or inversely, you’re a musician. How do you get to your fans?
  • 18. Only 10 years ago - pretty terrible. Buy a thing or borrow it.
  • 19. 5 years ago - a little better. Easier to self publish and discover.
  • 20. Today.The choices for distribution are immense.
  • 21. App developers are now the future of the music business.
  • 22. Good news: thousands of developers working on music. Bad news: most have been locked out of the business.
  • 24. Music platform Content Engineering Audience What a music platform gives you
  • 25. Music platform Content Engineering Audience Who can do what
  • 26. The power of APIs
  • 27. This is the Echo Nest’s business!
  • 28. Similarity Acoustic analysisArtist metrics Feeds RecommendationSearch / Tags Metadata Predictive analytics Content / Streaming So many possibilities all built into the plaftorm Fingerprint
  • 29. vibrant, active developer community developer API discovery playlisting mobile music games music visualizers remix apps analytics targeted marketing branded entertainment 100s of apps to date Not just independents-- the power is from partnerships
  • 30. Content / Streaming Where can I get audio from?
  • 31. Probably shouldn’t playYouTube videos Content / Streaming
  • 32. Or stream from blogs Content / Streaming
  • 33. Content / Streaming But the distributors & labels are getting there!
  • 34. Content / Streaming They believe in this as much as we do.
  • 35. Artist Mood Key Tempo Popularity Familiarity Location This Pandora competitor was built in 24 hours by one developer. It has 10 million songs available.
  • 36. An employee built this algorithm during a MHD Within a week there were 3 competing web apps for it.
  • 37. audiokicker is an upcoming iPhone app for social music
  • 38. audiokicker uses Echo Nest for recommendation and 7digital for content
  • 39. EN client streaming service Thumbplay
  • 40. All the potential is a bit baffling. This very inspired person is building “Frasier”-themed experiences. http://music.joshmillard.com/2010/06/04/nine-inch-niles-the-seattleward-spiral/
  • 41. There are hundreds of apps available on the platform already From big companies to one-person ideas
  • 42. Someone in this room is going to invent the way music is experienced in the future.