Info Reimplemementing and testing Khosla et al.’s MemNet, and beyond. Goals The original MemNet has proved difficult to use and access in recent years. We would like to implement it so that we can use their work for our own research.
Last winter, I worked on a personal project I call ongaku (from the Japanese for ‘music’). This was an attempt to use manifold learning to create a metric space for music.
This is an ongoing project to create 4X-style simulations of civilizations in a simulated world. This is intended to be a long-term project, that I will add to over the course of a long period, when I have some free time.
This is a project to look into the question: How do indie musicians use visual signs to indicate their subgenre? The main functions are in bandcamp_webtools.py, and do basic web scraping.
Overview Ongaku is a method for creating playlists programmatically, using only the content of the song alone. It uses gammatone cepstral analysis to create unique matrices to represent each song. A gammatone cepstrum is similar to the more common spectra used for audio analysis.