If you want mods like ITG's Marathon courses, I think I saw a few topics over at ITGFreak that'll help you with mods (and even rearranging the stationary arrows into a square ^.^) and placing them at correct times (they follow most the same rules as BPM changes, like if you wanted a speed change, throw in 0.000=x10 or something. (You can also throw in a banner with the same name.) Go to SM, Edit Courses, and you can do "Add an Entry" to add more Nonstop/Oni songs, set custom mods further below, etc., and SAVE YOUR COURSE. (your course name) and right below that, change Save As. Add the same things you would for making a simfile, but you only need Title/Subtitle. First, before booting, go into the SM directory, open the Courses folder and add a new text document. Players could also theoretically feed the system any song from their own music collections and be able to play it in StepMania.You want soundtracks? You got soundtracks!įor Endless I created a folder in the songs folder called "Endless Pack 1" (never bothered to make anymore) and put all the Endless songs I wanted in there. For experienced players who may get bored playing to the same tracks, the Dance Dance Convolution system could be a new way to change things up, and get new and varied choreography for a given song. The neural network works best (for now) at the higher skill levels, where there are more steps in a chart, and therefore more data to train the system on. This could be great news for people who like dance step games. On the other hand, there is some common structure in them.” Likewise, the Dance Dance Convolution system will produce a variety of charts for a given track, but those charts will tend to have some similar characteristics. He compared it to language translation: “If I give you a passage of text in one language, and you had 10 high-quality translators, they’d come up with 10 different translations.
One of the researchers, Zachary Lipton, explained that the concept of a “ground truth” is a little bit strange in the case of choreography. This also demonstrates a key part of the neural network’s advantage: It can produce many different charts for the same song. This demonstrates that the network is producing charts that are about as playable as human-choreographed ones. They differ, for sure, but you can see that Donahue, who was dancing to each chart, has a similar success rate at performing each one. The team has released a video comparing one of the Fraxtil charts to a generated chart of the same track. The results are encouraging, and the generated charts are playable. The second source is a collection called In the Groove, and it contains 133 songs that are choreographed for all but the highest level by a variety of authors. Fraxtil choreographed each track at all five difficulty levels, so there’s a lot of consistent data in that pool. The first and most useful is a set of 90 tracks choreographed by a prolific author who goes by the pseudonym Fraxtil. The system was trained on two sets of real-world data. Middle: The neural network's predicted next steps. Top: A real stepchart for Anamanaguchi's "Mess," choreographed by Fraxtil.
Instead, it samples every 10 milliseconds or so to determine what moments should correspond to steps. The step placement part is especially interesting the system skips the intermediate step of recognizing tempo or beat structure. Second, step selection determines which steps (left, right, up, down, etc.) to place.
First, it determines step placement - points in time at which there should be a step. I was playing with that for a while, and eventually it occurred to me that a much more interesting and novel problem might be to just try to recreate the game, rather than simply use the data as just sort of a convenient source.”Īnd that’s essentially what Dance Dance Convolution does. And I just had this idea to use that for tempo detection. “It sort of dawned on me one day that I had somewhere buried deep in my hard drive, gigabytes and gigabytes of data from this game StepMania, from a folder I’d been transferring from computer to computer since I was a teenager. But it occurred to him that StepMania packs already contain tons of annotated musical data. It’s notoriously difficult to obtain large samples of music with metadata about beat and tempo. The project began when Chris Donahue, longtime DDR player and machine learning researcher, was trying to solve one of the big problems in the field of music information retrieval (essentially, the extraction of data about music from recordings).
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