http://asymptoticlabs.com/enContents © 2022 <a href="mailto:quidditymaster@gmail.com">Tim Anderton</a> Wed, 31 Aug 2022 21:28:18 GMTNikola (getnikola.com)http://blogs.law.harvard.edu/tech/rsshttp://asymptoticlabs.com/posts/eigen-techno.htmlTim Anderton<div class="cell border-box-sizing text_cell rendered"><div class="prompt input_prompt"> </div><div class="inner_cell"> <div class="text_cell_render border-box-sizing rendered_html"> <p>I recently found an analysis of techno music using principal component analysis (PCA).</p> <p><a href="https://www.math.uci.edu/~isik/posts/Eigentechno.html">https://www.math.uci.edu/~isik/posts/Eigentechno.html</a></p> <p>The author, Umut Isik, extracted more than 90,000 clips of one bar worth of music from 10,000 different techno music tracks and stretched the music to all have the same tempo of 128 bpm. Then Isik fed those tracks through PCA and then analyzed the resulting principal vectors and the quality of music approximation with a growing number of components. Since the principal vectors are modeling sound we can listen to them which is rather fun. I won't cover all the same material as Isik did in that post and it is worth a read so nip over and give it a look if you haven't already. Isik has very kindly bundled up the source data and made it available for others to use (theres a link at the end of the post linked above). Playing around with such a fun data set is too tempting to resist so I'm going to do my own "eigentechno" analysis here.</p> <p><a href="http://asymptoticlabs.com/posts/eigen-techno.html">Read more…</a> (31 min remaining to read)</p></div></div></div></body></html> audiomusicPCAhttp://asymptoticlabs.com/posts/eigen-techno.htmlMon, 26 Mar 2018 14:24:13 GMT