Me: This vocabulary exercise would be so much easier if we could show pictures of sound!
John: You’d be pretty fucked if you were a blind music technology student.
Me: Wait but you would still be able to hear sound and you could turn pictures into sound and then listen to the visual representation of sound which would…oh.
My noise machine will be something like a barcode scanner except it turns image data into sound. There’s a lot of software out there that accomplishes this, eg Photosounder, Coagula, and Metasynth (and SPEAR for non-raster spectrogram), but I don’t think any of them does it in real-time (actually there probably is a way with Max but it’s not as flexible/efficient as I want it to be). It will be retrofitted onto a 2d rangefinder that my roommate and I hacked together for Build18, so it will be able to determine, not only color, but distance as well. So a given datapoint would contain information about color, distance, and horizontal (or vertical if the scanner is oriented vertically) position (in other words, a 5d vector: <r,g,b,d,x> or <h,s,l,d,x> or <h,s,v,d,x>)
I know, for certain, that low x will correspond to low frequencies, and high x will correspond to high frequencies, similar to a piano. It would also probably be in a logarithmic scale to correspond to pitches rather than linear frequency, since that is more intuitive/interesting to listen to. That being said, I’m uncertain about the mappings of all the other dimensions. I’m aiming for a machine that people can play around with, learn about sound in the frequency domain, and potentially be able to create rudimentary music with. One idea that came to mind was having the scanner be static and having a flexible whiteboard attached to a conveyor belt with a crank so people can draw sounds and intuitively play them back. Another idea is having distance mapped to amplitude so that frequencies would be louder the closer something is, allowing for playing around with physical objects and body parts.
Again, my noise machine is mostly based off of the Spectral Tablature, with some additional inspiration from my objective description of reduced listening and how I was having some difficulty explaining frequency analysis and spectrograms.