I am disappointed at the level of meaning we can find in our individual words. After trying some of the common words codes, I decided to try to focus on the meanings of word combinations, by rewriting the N-Gram text generator I was working with last semester in bit by bit in processing, which was based off of Heather Dewey Hagborg’s example in java. The N-Gram generator predicts the most common words to follow a given (N) number of other words. In this way, it can write a likely text by taking some two words, and analyzing a training text to find the next most probable word, then again for the last two words, and so on. I wanted to rewrite the code myself to incorporate some of the other subtractions, but I am far from done with that, so I used the code I used a combination of part of Dan O’s cleaning code to get rid of some of the uninteresting characters (though clearly not enough), and the code from last semester to predict the likelyhood of the following word, given a certain number of words to predict against. This generator, trained on my logged text from this week, produced the following likely text for me to write:
N=2:, to do it would look through phones or join forces via speakers ) ; println ( 200,0,200 100 ) ; println ( flushTimes ; int ( ) ; int [ ] = loadStrings floadStrings flushesnetworks data flush . itp . com vwww . edu telnet www . eud du ~ mr2868 telnet www . The applications of the best approach w rewrite the smoke outward camera setup until after our wor individual words . eud du ~ mr2868 69.89.27.236 v v v v v stmd > < > \ \ \ < > < esc > < esc > < de > \ del > es r Update on a a a training text file array String flushes . I think that is comparing eye movement toward each other questions ? I can be nice to see distinguish from the park anyway , it would be good animation in the park a different way , it will be tracked by taking some blou uetooth sensors . com v ; s s es r s s s s es r s s s s es es \ del > < esc > \ del ns lookup termni inal
N=3:were talking about experiementing s s int z z s ; impload smaria es function sketchProc ( processing { processing . pru ocessing . = function x } processing . pru ocessing . = function x } processing . por rocessin . g . c s v printl println ( flushTimes , ‘ , ‘ ) ; v v println ( flushTimes , ‘ , $ FlushArray ) sflushes . phps a smariarabi bnet ntet etworks . flushes . php c c2 . s sflushes . phps a smariarabi bnet ntet etworks . flushes . php . s sflushes . phps a smariarabi bnet ntet etworks . flushes . php c c2 . s sflushes . phps a smariarabi bnet ntet etworks . flushes . php c . s sflushes . phps a smariarabi bnet ntet etworks . flushes . lent gth ) ; v v println ( flushes . php mariar es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [ 0 ] es v flushes [
N=4 :I am supposed to meet for two pep separate group projects , so I used the code I had last semester to used predict prese idential addresses . is logged text from this week , this i I it prode cu uced T , trained the following likely text for me to write : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N = 3 : N =
N=5: INSTRUCTIONS make it interesting to watch , and the smoke thing seems really meditative , reminds me of laying on a fake patch of lawn and blowing smoke rings , from a cigaretet , e e , on a sunny day , This by the way , is what I think about when I think about smoke rings : meditative , wave like repetitive , soothing , etc . If somebody comes to find it because of spotting the s rings , or if they are in the park anyway , it would be nice to have something moving and thumping ( and possibly making the thumping sound mechanically instead of a with a speaker as well ) and blowing the f rings . The opposite would be finding the park and looking for the smoke , and finding a hole in the ground with no physical explanation of where the ms mso smoke is coming from or how it is generated . This would aslo be amazing , so as much aI as I would like to experiment with is wheterh her depth of focus can be tracked by using a camera on both eyes , therefore tracking
The texts get more interesting as N increases, which makes more sense since words have greater meaning in their context, but when the N is above 5, it becomes an exact replica of what I wrote after a certain point, for obvious statistical reasons with my limited set of training data. Still, there is a really interesting point right before this and after the complete nonsense, where the N generation brings something to light for me about the kinds of things I may have been likely to say, if my data this week was representative. I really like the switch in N5 from one piece of writing to the next, and the fact that there must have been obvious points of statistical correlation. I am going to keep building this data set and working on the edits in processing. I think this could be a really great way to begin building the robot version of myself that can eventually take over my digital life and take care of all that for me. . . hopefully.
