hfernand@andrew.cmu.edu – 18-090, Fall 2019

hfernand – Screaming Ring (Assignment 4)

hfernand@andrew.cmu.edu — Wed, 16 Oct 2019 13:02:58 +0000

For this assignment I attempted to create a ring of spheres that moves faster dependent on the incoming amplitudes from an FFT-ed signal. Using a modified version of the jit.mo organic example, I routed an incoming fft amplitude into the frequency and speed of position attributes for my circles. This means that the frequency and speed of their motion is directly impacted by the amplitude output of the FFT. Ultimately the result is a bit choppy, but I believe this can be attributed to frame dropping.

https://drive.google.com/open?id=1B5iahaCX-J2qdh0D5FXXVcFuQnt2_9Eg

Assignment 3 – Convolve The Girl

hfernand@andrew.cmu.edu — Wed, 02 Oct 2019 12:33:00 +0000

Using the code provided in lecture I convolved a sample of “Kiss The Girl” from The Little Mermaid with four different impulse response samples. The first two impulse responses were recordings of balloons popping in various locations. The first was recorded in a racquetball court and the second was recorded in the Doherty Hall A-Level hallway. The third sample used was a snare drum from a Dubstep sample pack. I chose this sample because I thought its intense and interesting characteristics would be interpreted interestingly with convolution. Finally, I convolved the song with itself to create a horrible reverby noisy mess. The four outputs are linked below, as well as a link to my code and audio files.

https://soundcloud.com/harke-official/p3-convolve-the-girl

https://drive.google.com/open?id=1z_9L-1SVYyMEaXSGvY9rVUS43RD-tb_A

hfernand – Arp Generator (Assignment 2)

hfernand@andrew.cmu.edu — Wed, 18 Sep 2019 07:00:53 +0000

Arpeggiation describes an instrument being played in quick and frequent notes. Using time shifting and the pitch adjustment object from the example patches I’ve created a Max patch that allows you to arpeggiate any sample. It works most effectively with individual notes of an instrument, but can be used to create interesting warping effects with more complicated samples.

Sample used is a free piano loop from Cymatics

Sample and code can be found here: https://drive.google.com/open?id=1GegSX5L9t_hepPwi–p9KOkjNO7kZuGr

hfernand – Assignment 1: Do Androids Dream of Electric Bill Gates?

hfernand@andrew.cmu.edu — Sun, 15 Sep 2019 20:52:09 +0000

DeepDream is a type of software created by Google to perform the reverse of facial recognition using a convolutional neural network. Effectively, a neural network trained to recognize faces, animals, or object takes an image and adjusts it slightly to “enhance” what it perceives to be patterns resembling the data it is trained on. A free piece of software that performs this task is available at deepdreamgenerator.com, and this is what I used for my found system. I used an image of the Gates Hillman Center from the Carnegie Mellon Press Kit, and ran it through the Deep Dream Generator 25 times. The Deep Dream generator has multiple options for neural networks that you can use, and different images that you can “train” the network on. I opted to use different network settings for different loops, as I didn’t want the final image to consist of only one type of pattern. This resulted in a highly warped image consisting of what appear to be dogs, fruits, and colorful spirals. In the video below I showcase each iteration of the generator’s output, and list the network setting I used.

The collection of produced images can be found here: https://drive.google.com/drive/folders/1gBPbAUWQjrRO948-1sF7Zf4l6LjDVhHp?usp=sharing