I feel lost when trying to get an overview of all the different MIR related services emerging monthly. Industry is moving extremely fast and coming up with solutions to problems which some researchers (like me) were trying to solve.
For example, I've done some work on algorithms that can classify genres by analyzing audio. The quality of the best algorithms I've seen is not so great. On an interesting music collection with several not completely obviously distinguishable genres (obvious like techno vs. death metal) the algorithms perform a lot worse than humans. Why bother with that if a better solution already exists? With a better solution I mean one that is not limited to only genres, one that assigns multiple categories to each item: tagging by people. If you doubt it, you might want to check out the last.fm tags. I (and many other researchers) have been checking them out recently (check out Paul’s blog for some interesting ideas and comments on tagging).
So instead of trying to do some simple mathematics to understand music, just give millions of users the option to tag songs and artists (and give them benefits for doing so). If you don't trust the masses, hire experts. If you think I'm kidding check out pandora.com. If my ears didn't fail me, Tim Westergreen (founder of pandora.com) recently said in an interview that they got 600.000 tracks in their database. He also once mentioned that it takes an expert 20 minutes to annotate each track. (100 person years of work - if it’s true. Spare a moment to think of all the wonderful MIR research things you could do with that kind of data.)
Btw, it's not just music classification that seems solved. You’ll find services that successfully create playlists, give recommendations, ...
I'd also dare to say that it's not just stuff I've been working on that seems to be outrun by industry. Have you ever tried Midomi query-by-humming (or singing, or whistling)? It works!
People in the MIR research community have been working on query-by-humming for many years. As far as I know the mainstream research direction was to extract the melody information from human input, and compare it to melody information extracted from the music, and match them.
I know nothing about query-by-humming research. However, I've seen demonstrations and the results were not so great. Some people (like me) don’t sing/hum accurately enough. Furthermore, extracting melody information from songs is a lot harder than it seems. So while researchers were working on the problem and envisioning how great a system would be that allows you to query a large archive by humming, the problem was solved by Midomi.
Midomi found a shortcut to the problem. Instead of relying on computers that understand music, they found a clever way to use the information humans can give them easily. (For an interesting analysis check out Cristian Francu’s post on the music-ir list on 2007/02/02.)
I'm not saying that any of the research was wasted. Not one second of it! Extracting (and matching) melody information is extremely interesting. It's a big step towards truly understanding music. Also developing algorithms that can analyze music and classify it into styles/genres/moods will always remain an extremely interesting research direction, despite tagging. However, it seems that in some cases the motivation for our work needs to be reformulated.
Or maybe MIR research should just give up? Wait and see what industry comes up with and then solve the problems that are left over?
Well, I got to continue writing my ISMIR paper now... which btw is my answer to all these questions :-)
And I hope everyone else is busy writing their ISMIR papers, too.