I claim to be biking 30plus Ms 2day w.RossandJack, but 2ms to MrktEast and my stomach is in revolt. Hopefully just nerves, or i am going 2b unhappy on hiway…
Archives for July 2006
and when inspiration finally hits you it barely even breaks your fall
I’ve heard – from people who both teach and live their songwriting – that you have to keep the muscles limber. Just like an athelete who runs a meaningless mile around and around his block, you have to keep the words flowing all the time so that you’re ready to catch the next best thought you have in a butterfly net of carefully trained artistic reflexes.
It sounds like a wonderful idea, except i don’t like writing throwaway songs. I’m certainly capable of it, but i find it a little offensive – all that creative output and effort for something that just takes up space on my list of titles – i don’t want to hear or play it again, let alone pass it off to an unsuspecting audience.
I like to think instead that the more rarified that pen-to-pad impulse becomes, the more remarkable the results. Why wade through daily crap when you can have a monthly gem.
The monthly gem, as it turns out, seems to be a myth when you are a well-fed gainfully employed yuppy. Because, you are complacently waiting for inspiration to hit you, but inspiration typically needs a life event to set it into motion, and you might not be having so much of those, perhaps?
Back to those limber muscles, the value of which i am coming to understand. The trick, you see, is to refuse to write something to be thrownaway. Don’t just write aimless words. Pick a topic with legs. I’ve decided that, for lack of other inspiration, i will write a song about everyone i know. Some of the songs might suck, and they might not even correspond to people who suck. At least Elise will get a break from being the topic. Gina somehow got (apparently) the catchiest song i have written, ever. One of my least favorite people ever got sortof a funky love song. Neither seem to be a coincidence. And, this shit just keeps happening.
Now I’ve got a pile of maybe songs, some about people who really shouldn’t be told they are the topic/target because songs are so much better when they’re a little scandalous so i find i keep telling the truth in them (note to self: stop titling with people’s names). None, though, none with tight enough screws to hold the weight of me and my guitar. So, i am not declaring them done. Simple, no? Every night i come back to the gaggle to polish – write a better line where i can, restart the progression in a different tuning where it might work better. Maybe i can get one to graduate to being a real song, someday.
Working on the new lyrics MYSQL backend i now know fo sho that i have 200 songs (yes, with the help of technology we’ve finally eeked it up from 144). That averages out to 25 a year, but really it’s more like 32 a year for a while, and only a handful this last year and a half. But now i have all these half-formed things circling like little audio-vultures, picking my brain for better ideas.
I bear no promises of audio samples or lyric sneak peeks. Yet. You just have to trust me on this one.
Closed Loop
This post will (temporarily, at least) close the loop my recent discussion of good music prediction systems.
One service that initially escaped my attention was Last FM, aka AudioScrobbler. Perhaps it went unmentioned because it’s a bit of a hodgepodge when it comes to features – it tracks what you listen to, but compiles only the vaguest (and in my experience, often incorrect) statistics about your listening habits. It features some free music, but not in a predictable enough fasion that i’d use it on a regular basis.
Since it doesn’t accumulate anything but playcounts, Last.fm can only predict based on your listening habits. For someone like me who listens to 1k+ tracks a month, the approach is fascinating but ultimately scattershot, as it isn’t weighting my likes and dislikes at all. Though it has the plus side of offering predictions based on a large network of users who you can either friend or “neighbor,” the lack of any rating scheme is a major turnoff.
That said, i return my attention to Yahoo’s LaunchCast Radio.
I have been phasing this out at work now that I have a new iPod, and it’s unaccessible at home since it doesn’t work in Firefox. However, i remain convinced that it comes the closest to being the best music service out there based on the strength of its predictive abilities. It has lead me to more than a few downloads and purchases in the last month, many of which have been surprisingly obscure.
I definitely recommending trying the service, and do so with the following recommendations:
- When you first subscribe spend a day or two listening to one of the pre-set stations that’s nearest to your tastes in order to give the service some ratings to work with. Alternately, take a sampling of your record collection and add 200-500 ratings – probably enough for the services correlative powers to kick in.
- Unless you enjoy a *wide* swath of music in one particular genre it’s in your best interest to rate genres very conservatively, especially high-level buckets like “Rock” or “R&B.” Rating “Rock” highly partially thwarts a rating of “Don’t Play” for “Classic Rock.” Furthermore, the system seems to prefer genre recommendations to song correlations, which is increasingly frustrating as you fine-tune your song ratings. Just as bad, if not worse, if you leave genres blank Yahoo assumes you like them all equally!
- One positive impact is that if you have a subgenre you’re interested in hearing more of, like “Big Band” or “Zydeco,” you can rank it heavily for a few days to get served a bigger sampling of songs so you can develop your opinion.
- Similarly, only rate an artist if you want them to impact the system’s choices. You might love Madonna or Depeche Mode, but if you aren’t interested in the terrible pop they’re correlated to you might be safer just rating songs and albums. Rating a smattering of songs by an artist has an equal (or better) effect on being served more songs by the same artist as rating the artist themselves.
- Whenever you hear a song you really like, click the song name to view its entry, which contains its similar songs. This is especially fun when listening to classic music that you don’t necessarily own, as it tends to jog your memory for other songs you’ve forgotten. (When you hear a song you really hate you should do the same thing; you might kill ten terrible-sounding birds with one well place stone. Or, you could find out a song you love is too closely correlated to the distasteful pick).
- There’s a fixed amount of time (or number of songs?) you can consume in any given month before higher features are locked out, leaving you only with your own station with a somewhat limited pool of songs. Our office seems to hit this point about 2/3 into a month. If your tastes run mainstream the limited pool is actually not so bad, but to avoid this make sure to shut (or at least pause) the player when you leave your desk.
- Though Yahoo’s awesome correlations per Artist, Album, or Song help support predictions of your taste, the system seems to be incapable of adapting to a non-standard correlative scheme on a per-user basis.
For example, what if I rate “Don’t Play” on every song over five minutes? The system would learn to avoid long songs that were similar to each other, but voting no to Queen’s “Bohemian Rhapsody” and LedZep’s “Stairway to Heaven” wouldn’t necessarily protect me from Fiona’s “Never Is a Promise” or Tori’s “Yes, Anastasia.”
A best-of-class predictive system would be able to determine your tastes not only based on correlated predictive data, but also based on your personal trend of ratings for certain song lengths, BPMs, producers, labels, or even mix levels and/or frequency response.
If you know of this promised land of music consumption, please point me in the right direction. Heaven forbid i learn enough programming/scripting to be dangerous, i might have a go at my own datamart, a la iTunes Registry.
a stronger faster fiercer me
I would just like to point out, tipsy as i am in the wake of viewing Dead Man’s Chest, that i am still quite possibly the worldwide master of amateur Ani DiFranco transcribers.
Was i comfortable resting on my laurels of years gone by, having accurately transcribed the better half of Little Plastic Castle prior to release? Or, relying on my collaborative transcription of the good bits reveling/Reckoning to tide me through more fallow years? No, my friends. Because, as i have just reminded myself (and also the world, via this post), i am still able to choose an Ani DiFranco song to play on one day, and am able to play that very song the very next day.
I scoff at pre-printed tunings and stabbed-at tabs in standard – they’re meaningless. I learned the lazy way to play guitar from the best rabid feminist with glue-on nails in the business; i can suss out the easiest tuning out of any grouping as soon as i figure out the open strings.
Meanwhile, Depp and Co. scored a big 3 Drinks, 3.5 Stars from me after tonight’s viewing. I fairly actively despised their debut flick, but after a tumultuously awful start this go wound up thrilling fun, just as all summer movies should be. Superman will need much luck (and maybe an extra drink?) to best them in tomorrow’s viewing.
A Picture Share!
St L’s utterly superb KitchenK; two meals and not a bad bite yet.