Final Presentation | Data bending and Transcoding in 8 channels by Nick Karalexis

The final presentation of this work is a soundscape in 8 channels. The piece is the sonification of two different graphic works. The first work was drawn in Adobe Illustrator and then manipulated as raw data in Audacity, resulting in the second piece. Four channels contain the original image and the other four contain the manipulated data. Uploaded to the Soundcloud playlist below is a track for each speaker channel. A simple patch in Max MSP was used to playback the piece in 8 channels.

Abandoned in Place | Sonic Elements by Nick Karalexis

For the RPI Arts Undergraduate Exhibition, Still Rendering, my piece was called Abandoned in Place. It was a piece on media obsolesce and the ideas surrounding transcoding and glitch. The installation contained 4 channels of audio, image work, and dead media to tie the piece together. The audio was the sonification of the image in the light box, (30x30 print, 1 hour per channel, on loop).

IMG_0064.JPG

Sonification - Final Images by Nick Karalexis

Final Images used in sonfication project. These image are evocative of media degradation and obsolescence. The process used to sonfiy the data is reminiscent of analog distortion and artifacts found in analog media such as tape and film.

Notes from Class by Nick Karalexis

Notes from discussion:

  • Look at IEEVR (http://ieeevr.org/2019/), Rob ran into some interesting panels/projects relating to transcoding and tying visuals to audio

  • Controlling the black box could be more important than knowing a ton about how it works

  • What happens when you import data into different DAWs?

    • Try protools, reaper, etc.

    • Look for what is different, and maybe try to explain them, but more importantly, think about how to use the results as a tool.

Articles and sources:

  • http://blog.animalswithinanimals.com/2008/09/databending-and-glitch-art-primer-part.html

  • ieevr.org

Encoding/Decoding Methods by Nick Karalexis

I did some research on encoding and decoding algorithms. There are two that generally yield interesting results, u-Law (or “mu”-law) and A-law.

Information regarding how each of these methods work is can be found here and here. The idea is that some encoding methods allow for larger dynamic ranges than others and thus yield different results.

The original image, a simple red square, shown below, was used in testing and the resulting signification is below. As you can see in the included wave form and hear, the audio encoded with A-Law has a larger range in terms of amplitude, which makes sense as the dynamic range of this algorithm is greater than that of U-Law.

Red.jpg
Wave form of above clips

Wave form of above clips

Update - Separated by Color by Nick Karalexis

Over the last week, I worked on exporting images with only one color channel active, in order to create multiple tracks. I’ve also tried many different encoding algorithms to see how they affect the output audio.

I used photoshop to separate out the Red, Green and Blue channels of the image as raw data.

First, Photoshop files were decoded, and the raw data is encoded as audio. This method was not successful, I couldn’t get anything that didn’t sound like white noise.

One track uploaded is raw data, exported from photoshop (.psraw) with the right channel as the “blue image” and the left channel as the “green image”.

The other track is PS files exported as Bitmaps, which created some interesting sounds.

I also messed with pushing sound to the ring of 8 in West 118, but someone messed up the routing table on the X32, and I got sad.

Update — Week 3 by Nick Karalexis

This week I looked at some of my past work and read up on different signification techniques. I’m posting some of this work, as well as some early attempts at sonifying some of my imagery.

aMS_01.jpg

Past Work

This past work is an example of the style of the greater piece I’m creating. This former project inspired me to create a series of test images to explore what data bending could sound like.


Below is are a series of test images I made. When each image is exported as raw data, it can be interpreted as sound using a DAW. The audio clip below is an excerpt of this.

Scholarly sources to consider by Nick Karalexis

Below are some sources that I’m looking at. Some texts are also cited in my thesis regarding critical design, media death, etc.

Sound Unbound: Sampling Digital Music and Culture edited by Paul D. Miller

The Death of Art by Bhesham R. Sharma

Homage to New York, the self destroying sculpture - an artwork by Jean Tinguely w/ MoMA (1960)

Raster Scanning

The Signification Handbook

Will be looking towards Rob to find sources that will aid in the actually signification process.

First ideas... by Nick Karalexis

For this project, I’m looking to sonify data from my senior thesis project. Then, I’d like to incorporate this soundscape into the project for my senior exhibition.

My thesis project revolves around media death - what happens when the medium that holds our art becomes obsolete. Through creative seminar, I’m exploring and showing this process. In a nutshell, I’d like to use the project in this class to hear what this process sounds like.