Hello!
If you want to use a pre-existing database of audio, searchable from a
developer API:
http://the.echonest.com/
'The Echo Nest knows more about music content and consumers than
anyone. Our platform opens up this dynamic music data to any developer
through our easy-to-use, real-time API'
http://www.freesound.org/
'With the Freesound API you can browse, search, and retrieve
information about Freesound users, packs, and the sounds themselves of
course. You can also find similar sounds to a given target (based on
content analysis) and retrieve automatically extracted features from
audio files.'
a big list of audio apis of various sorts
http://blog.programmableweb.com/2012/01/18/160-music-apis/
best
Matthew
On 19 April 2012 16:06, Al Matthews <prolepsis_at_gmail.com> wrote:
> Bryan Pardo at Northwestern and Parag Chordia at gatech do some nice
> work, for example.
>
> http://musictechnology.northwestern.edu/faculty.php
> http://www.gtcmt.gatech.edu/
>
> On Thu, Apr 19, 2012 at 10:33 AM, alex <alex_at_idoia.com> wrote:
>> Very good.
>> Thanks a lot.
>> Alex
>> Le 19 avr. 2012 à 16:31, Richard Lewis a écrit :
>>
>>> At Thu, 19 Apr 2012 15:46:34 +0200,
>>> alex wrote:
>>>
>>>> I was looking for an audio search engine when I realized that I did
>>>> not know any that was as much known as google for text and document
>>>> or vimeo for video or again flicker for still images. I read a short
>>>> page on wikipedia that talks about 2 algorithm approaches, one
>>>> searching in the metadata for keywords (not that interesting to me)
>>>> and some others (without links) trying to differentiate speech form
>>>> music in the body-content of an audio file for example. I thought
>>>> the good place to ask such a question was here. Maybe you are all
>>>> aware of projects like this, Apologise for not having read the
>>>> archives.
>>>
>>> The Online Music Recognition and Search project conducted at
>>> Goldsmiths' College and Queen Mary, University of London delivered a
>>> tool called AudioDB. It's a essentially a feature vector database
>>> which uses locality sensitive hashing to find approxiamte nearest
>>> neighbours to a given query vector.
>>>
>>> http://www.omras2.org/audioDB
>>>
>>> The code is very much research-grade; it works, but you have to
>>> compile it yourself and there's little documentation. It's written in
>>> C++ within bindings for a few other languages.
>>>
>>> Another important caveat is that it's not (like Google, Flickr, etc.)
>>> a search engine over an existing database. If you want to use it, you
>>> have to create your own database. And to do this, you need a feature
>>> extractor to get features from your audio collection. You also need an
>>> audio collection. The same research project also produced a simple
>>> extractor called fftExtract:
>>>
>>> http://omras2.doc.gold.ac.uk/software/fftextract/
>>>
>>> As an alternative, you may be interested in looking at the echonest
>>> API, see especially their track API:
>>>
>>> http://developer.echonest.com/docs/v4/track.html
>>>
>>> It also occured to me to check if Shazam publish an API. I couldn't
>>> find one.
>>>
>>> Best,
>>> Richard
>>>
>>
>
>
>
> --
> Al Matthews
>
Received on Fri Apr 20 2012 - 11:43:43 BST