Yes it is: http://www.musipedia.org/whistle.0.html

Ah ha – is this it?
http://www.musipedia.org/whistle.0.html

http://www.dlib.org/dlib/may97/meldex/05witten.html

old input, but very interesting. i must smile, if you compare may 1997 and today

Andre

Tetsuya Kageyama, Kazuhiro Mochizuki, and Yosuke Takashima: Melody Retrieval with Humming, Proceedings of the 1993 International Computer Music Conference, pp.349-351, September 1993.

Unfortunately, it is completely in japanese, so not a lot of people (myself included) have read it. After that, probably the most well-known work is a 1997 paper from the New Zealand Digital Library project. Here is the paper:

http://www.dlib.org/dlib/may97/meldex/05witten.html

And here is a website with the implementation (java required). Note (pun not intended) that input can be either by piano keyboard or hummed audio.

Since that time there has been an explosion of such systems. This list is large, but I can think offhand of a few systems it misses:

http://mirsystems.info/index.php?id=402

But other than that.. why limit your imagination to query by humming? There are so many different ways of doing content-based music retrieval. How about query by tapping for rhythm retrieval? How about query by genre for finding new music in the same style as music you already like? How about query by instrument timbre, so that you can find other songs that use that driving guitar you really like? Or query by vocal timbre, so you can find that Paul Weller song in which Paul McCartney sings backup, largely uncredited in most metadata sources available?

There is so much cool stuff being done right now in this area. The community has largely moved beyond query by humming onto more ambitious research and projects. Check it out: http://www.music-ir.org/

No, sorry

BB

I first came across it when someone (I think Edd Dumbill) linked to imgSeek a couple of years back; imgSeek is a standalone image management application that incorporates the same algorithm. retrievr is a new implementation in pure Python (plus a host of great libraries: PIL, aggdraw and numarray).

In my experience, the results are usually fairly good, sometimes even stunning – considering the artistic sophistication most of us are able to come up with (gallery forthcoming); and in the cases they’re not so stellar, they are at least entertaining But clearly, the approach has its limits.

One thing to keep in mind is that it doesn’t do object/face/text recognition of any kind, so if you’re drawing an outline sketch of a chair (or corporate logos like Tara Calishain has tried), it almost certainly won’t get you one back (except your index only contains images of chairs). It helps to think of it as matching the most pronounced slabs of colors. Another thing to know is that there’s currently no way to specify the aspect ratio, so you have to rescale the image in your head (things that are close to the borders of the image you’re thinking of should be close to the borders of your sketches), but that’s really just a missing feature of the drawing flashlet than an inherent problem. Sometimes it also helps to _remove_ detail instead of adding it. And finally, the index covers only about 85k of Flickr’s “most interesting” images at the moment (I didn’t want to use up even more of their resources before checking back with them; it’s fantastic enough that Flickr isn’t imposing any up-front limits on API usage like most everyone else is doing).

In a way, I see retrievr less as a “search” tool than an “exploration” tool, and it seems to work very well for that.

I think the idea is good, would also be cool if somebody did something similar for music/sound.