song/identify supported both ENMFP and Echoprint, and AFAIK the Echoprint matching path was exactly the same as is published on Github.
I know at some point we did adapt the Solr end (for example, we removed the N most occurring codes) for speed optimizations.
Many users of Echoprint in the wild have adapted the python matching logic for their use case as well as changed the hash update rate on the codegen. A great modification to watch was Sunlight Labs' "Ad Hawk", which ID'd commercials: https://github.com/sunlightlabs/adhawk
I like this concept, but you need some sort of automated filtering. My first track (because hypem liked it) is a cat purring.
Plug but it's a useful one: run the tracks through the SCAnalyzer http://labs.echonest.com/SCAnalyzer/index.html and filter for speechiness and duration. If you get a SO ID, you'll also know the artist via fingerprinting and you can do more filtering at that level.
we're adding j-core now, thanks for the suggestion!
sxsw is why this is special, we will be adding and changing these over time. It's clear that genres don't have to directly correlate with musical style.
These genres come from people talking about music using whatever organic / natural words they use to describe music. We've done the work to map those into single-term "genres," as it's been shown many listeners appreciate the flat categorization. There are similarities between genres in the API, so you can quickly see which genres sound like others.
Analyze your own, it'll be much better when you're doing synchronous stuff like this. Our canonical audio is likely very different in bitrate or time to start.
Yes: you can use Echo Nest Remix in python or do what paul did and pre-load the analysis and do the playback via webaudio. Remix takes care of the chopping at the right bits for you: http://echonest.github.com/remix/
hah -- any one of you would do the same faced with an overzealous auto-linker js on IRCCloud, a discussion there about the README.md it points to and access to a corporate credit card. it was very funny at the time, i promise. here's our "announcement": http://blog.echonest.com/post/9332881544/new-pyechonest-on-g...
The article says "He quoted an NBC spokesman as saying: "Our social media department was actually alerted to it by Twitter and then we filled out the form and submitted it."
I can read this in one of two ways: Twitter (the company) alerted NBC, or Twitter users on the social network Twitter alerted NBC. There's not much clarity there, but obviously the former is scary and confusing and the latter happens all the time.
My reading of this is a complete miscommunication. Nowhere in Apple's email does it state they had a problem with content. I really have no idea how she jumped to that conclusion. The very simple and likely explanations are either (1) she did not remove all links or (2) the reviewer did not closely check to see if she removed all links.
Don't see any emails about the content block that she is referring to this post. I see emails about previous issues of her having links to Amazon in her ebooks. I am very curious about this, because I doubt just saying the word "Amazon" can really be an instant rejection -- and a quick search of the iBook store shows tons of books about Amazon itself, things like "How to Self Publish on the Amazon Kindle" et al.
dalton, i saw a dear friend support you over my twitter and I clicked but have NO IDEA what this does? Seriously, I am pretty internet savvy but all I read was "feed platform" and how you weren't going to sell my data-- but what data? What is it? you might want to update the landing page a bit :)
I was very upset when I saw that result but a good scientist never shows his bias :(
I do really think that once we get better at "artist evolvement" (separating Pink Floyd into two or three separate artists as they had very distinct phases) the PF signifier will drop. I only listen to Syd and "It Would Be So Nice" era PF and definitely am not a Romney booster.
I know at some point we did adapt the Solr end (for example, we removed the N most occurring codes) for speed optimizations.
Many users of Echoprint in the wild have adapted the python matching logic for their use case as well as changed the hash update rate on the codegen. A great modification to watch was Sunlight Labs' "Ad Hawk", which ID'd commercials: https://github.com/sunlightlabs/adhawk