Category Archives: Assignments

Project 1 – Kun Peng

In this project, I explored the harmony and intervals in midi files and visualized these qualities. Each midi note is represented by a cube, which is pressed down/pulled up when the note is turned on/off. A noise value relevant to the dissonance of the chord currently held is generated and applied to the position attribute of the cubes. The rendered mesh object changes its color mode when there is a root-note change detected in the chord. Unfortunately, the visualization is pretty crude and I’m still very far from what I wanted to do. I had some troubles trying to manipulate each cube independently in a more creative way under jit.gl.mult context, for example, applying a glow effect on a specific cube when a note is turned on. My major plan is to improve my methods of generating the cubes so that ultimately they can be manipulated independently.

This part of the patch evaluates the intervals in a currently-held chord and assigns a dissonance value to it. The current evaluation is subjective and cannot accommodate inversions or the subtle differences in complex chords. For future work, I will integrate the material discussed in this note and produce more robust evaluations. http://www.oneonta.edu/faculty/legnamo/theorist/density/density.html

This part of the patch generates the noise value and applies it to the position matrix.

 

A short demonstration of the patch(I know the visualization still looks too simple; I will work on more ways to integrate the signal processed into the rendered objects).

 

Project 1 – Matthew Xie

For Project 1, I created a self-generated melody & drone patch.

First off, a wav file of single piano notes played consecutively is analyzed. While Max randomly selects portions of the wav file to play in snippets, the frequency of the audio being played is analyzed and triggers the 1st higher-pitched drones in intervals. Meanwhile, the 2nd drone patch can be triggered by using the keyboard as a midi-keyboard.

The drone is achieved via subtractive synthesis. The pink noise generator is send through filters, only letting pass certain frequency bands. Then, the subtractive synthesis is done with a handful of inline reson~ objects.

The ‘analyzer~’ object is referenced from the maxobject.com website.

Delay is added to all sound effects. Piano melody can also go through a noise gate at will. The speed of the piano sampling can also be manipulated, which will immediately also effect the speed of the self-generated higher pitched drones.

Here is an example of the music being played:

Code is Here:

Reactive Visuals in Max for Live (Project 1) — Jonathan Cavell

For our first longer term project, I created a patch which resulted in a more stylistic visual which reacted to midi and audio data from Ableton Live session information. Within the patch, gl objects are set to render and erase based of midi information from each instrument and are manipulate by the amplitude of the audio signal generated by each instrument. The end result is a set of shapes/objects, each assigned to their own instrument, which are turned on and off by that instrument and manipulated by its audio signal.

The patch automates the movement, transparency, and rotation of objects within the video window in direct proportion to the amplitude signal of each midi instrument in Live. For the shapes associate with the synth, I created an image in Adobe Illustrator which was then imported into Max and layered to create a new object. The drum kit uses clearly defined geometric shapes to contrast the more amorphous shape generated by the synth.

Midi Send Portions of the Patch

Synth Visual Portion of the Patch

Drum Visual Portion of the Patch

The patch itself, while it is rather large (and divided into a set of four patches within the Live session) is built on a series of smaller patches to execute a simple, but polished concept. My personal goal for this project was to become familiar with a set of techniques which I had not utilized in a previous project and familiarize myself with the Max for Live environment which operates with a unique set of limitations. I wanted to create a patch that generated a stylistic visual element which could be replicated for live performance which came across as a more polished visualization with smoother transitions than what I was able to achieve in previous projects.

Of these techniques, the ones I was most concerned about ended up being the easiest (ex. creating a unique shape/image in Adobe Illustrator and converting it into an .obj for use by jit.gl since I do not have a visual media background) and the ones I thought I should be able to complete easily proved more complicated when working in the Max for Live environment (ex. automating the transparency of different jit.gl objects and creating smooth movement across the video window).

I would like to experiment further with the automation to create a much more experimental version of the visual elements, but I am pleased with how this first version turned out.

Drum Visualization Patch

Synth Visualization Patch

Midi Send Patches

Project 1 – 3x Oscillator – Will Walters

For this project, I created a synthesizer instrument called a 3x Oscillator. It does more or less what it says on the tin, the user can control three oscillators which can be played via midi input. When a note is played, the oscillators produce sound in tandem, creating a far fuller sound than a single tone. The oscillators can be tuned and equalized relative to each other, and the waveform of each can be selected – sinusoid, sawtooth, or square. Other options for customization include total gain of the instrument; independent control of the attack, decay, sustain, and release; and a filter with both type and parameters customizable.

Here’s a video of me noodling around with it:

(sorry about the audio in some places, it’s my capture, not the patch itself)

The main patch can be found here.

The patch used inside poly~ can be found here.

Project 1 – Kinect Depth Projection Mapping – Adam J. Thompson

This project was an exploration of how the Kinect might be used to map pre-rendered and generative audio-responsive projections onto the faces of instruments.

The patch uses adjustable maximum and minimum Kinect depth map thresholds to isolate the desired object/projection surface, and subsequently uses the created depth map as a mask. This forces the video content to show through only in the shape of the isolated surface.

The patch is less precise on instruments which expose a large part of the body, as, for example, legs tend to inhabit similar depth thresholds as the face of a guitar; it is better suited to instruments with larger faces that obscure most of the body, such as cellos and upright basses.

In attempting to map to the surface of a guitar, I also toyed around with other uses for the patch, which include this animated depth shadow, which places the video mapped shadow of the performer on the wall, creating the potential for visual duets between any number of performers and mediated versions of their bodies.

I plan to continue exploring how to make this patch more precise on a variety of instruments, possibly by pairing this existing process with computer vision, motion tracking, and/or IR sensor elements.

The gist is here.

Jonathan Namovic Project 1- Launch Pad

For my project 1 I decided to try and make an instrument out of my computer. I separated out the keys into distinct regions and assigned them midi values based on where they were on the keyboard. I then used these note values in different modes to produce different sounds. I also included a boomerang effect that allows the user to record a short piece of audio and then the patch loops it and repeatedly plays it. I created ten drum sound effects by filtering noise in different ways. The main instrument portion is a square wave filtered in a similar way to make the note sound less harsh. The last mode is a saw tooth tremolo that repeated plays the same not so long as it is held. The launch pad is polyphonic and can export the sound in the loop buffer.

A short example piece that has been layered three times

main patch code:

note maker code:

drum patch code:

saw tooth tremolo code:

Project 1 – Isha Iyer

For project 1, I used a Kinect to control the motion of a particle system using my hand. I am very interested in different applications of motion tracking and I think this was a good introduction to help me learn how the Kinect works. Here is a download link to a video showing my project in real time: IMG_1479

I used this tutorial to help me create particles from an image that I would then control using input from the Kinect. To control the Kinect I used output from the object dp.kinect2. This took me a while to set up initially. I wanted to have the system use real-time image input from the Kinect as the image – that did not end up working quite like I wanted so I stuck to using one preset image.

Here is the gist for my code:

 

Project 1 – Automated Lighting System

This patch analyzes audio in three ways and represents the information through a LED light pattern.
The 30 LED lights are grouped into three subgroups, where there’s an inner layer consist of two lights, a middle layer consist of a ring of 10 lights, and an outer layer of 18 lights. Changes of colors or brightness happen from the inner ring to the outer ring, so that the light propagates outwards.
The audio amplitude controls the brightness(saturation) of the colors. The ratio of lower frequency to higher frequency controls a color picker, which determines the RGB values. Then the values are being sent to the three layers with different amount of delay.

Code:


----------begin_max5_patcher----------
6718.3oc6csrjiiakccVeEJz3UyjEGbwaLgWXGyV2q7JGU3nBlRLyhcSIpQh
pdXG1e6C.3akjTfRfJUWIqtCUpHHE.N7fKtu.v+7COr7ozuGcX4h+mEeZwCO
7O+vCOXuj4BOT7ueX4lvuuJI7f81V9bR51iaV9XdQGx9QRj85kWQWX5wrjnL
6siKtZ9kx9wtn75Re6KV9T31WVt3uWbKOmteSXloXdwU1Els5Kwae4y6iVkk
+b.kSBjDBQPebAkfB3bk7wERT.5wEXR.p5mKdssYk9zu9Q7xpev8gahxh1+4
nsgOk2vQ0s63skMavbs+0G9f4iGcDX1F8MckUVUYQe21jWdXWTz5j3M5lNxU
TC5E0p5dcgMLFJPQkTI+wE.HDABEhgEOtPIFBd..srKP.OEf.ZxAAIKfV.BR
IwzwGt6yX2tdO9V16ADQSAvBrhcNLfJlZLHIMb8lnCGtAL.fRM8UNBEv3JAB
etdOWtbhEBb658JFZbcdFwacdSOL7knW06QKz+2z1swHIOPvQXF0P7AlVPHi
wzx9.BcPgeHo2n9C1+e+7ek8+j3sQqROt0BBzocLOBnAjB0B.rVHHlJTXsbO
lfYGOH690OY5E9uJLIZAJ.X5OjlOV.AudvP9S+2hRRR+1GgICaDBnPkIfisi
Kn8nyT2.C2i.yWe9euPnENcYfAsOv3P7KaCSL5WNv2FDvvHsrDMfYfIBkGnz
BRMhRD7gPLnGtDwmRRBVj++cQg76jnbcmkgPTkQdJhDnGKgER8jJbAEOf7Th
+Tl7oiYYoau5NZayL5nyxUTS2SRUAJsAFBR9K4AdUK71bluslSozuX45+HMr
aEDPvJNCzRMQCOmo3lXQ0aL1nZXoIEqoFm2RSffeGfLBAxLdQamQfPpXFBCe
XkrpmMYRgkdEaNwBKMxGKmgkgkAZAkTiPxgGFoldMO4josmKHJCSPSALczg6
tDvac2eMNK34cGd4X7XGB7b51rmCW0h1Yt1g3+g8ZfQonAFsLLZHUURL.BXG
R.BqZVjdz+jWII0zJ1pGZXK5WR2FtJ0aSxbimHUKEDJm9r+IQ4reRlDUp0Kr
bzOWwO+HAfPdGLKA.fzZ5kSPBV8V5j1rEvhmtZfJVap6iNLLQPspSqMLCryi
Nn+YHpo14TFoo5Wm6i+9hj3W9R1uj+c5hUeIb+BB5pwEcE747J3rhPKUEWJB
XRIn3F4GvfNuapgmCQIKVmtM50vv21fQ.CwvnvQhHVJxYmNImlnzhWLdyv3R
WtbPW4wmZmY7+oGXtOcAFu3OEtJK9qQKfK.Vt5IXD5+hhEVK0fyL7QN0Xx+H
YwK6SOtym7CWGm.HJOfiUXA9bjioOHOF4HwZ41W.PPFDHbDLTZkQwRPnTmEK
v9ym2GSxhOjDu1w9cshlnAoDGpggxa7oWVkljtOuOamMs9CnQG8LroUZEMWG
lE1bj3.LL.ICTLJkqM9khQ0J3BB824HdmdOzIGDn6iZzWCmM5RXFqQWYpjoG
uYWP39rsQYAF3XeZRRzdsLsiYoZMA9SG2FuJ7PViu943c5AaAh.fIC.I6MYv
Nlo+aoVUIkQogAY3X5TOs3+sO7AoVCUidjN68ZBDH4bIFzVToFVZ2jKt6+RS
XuI..gdp4EC22UpotquKb0uk6H5k2tv5H0BhLtpDoY+4w0uWUBIStiU9CvBb
Wgxc5BiSKqLaDcW1fFYyl9.6GuMpShfKPwkKSrEbnUBBJXFbXP3P5sPzzqXQ
yLXdlXbdoDMgCFGEPQDjfeN1A2eBIWGahuVgFFIw6ZMO+YPgRchvLd.ZRQFj
JPP3DoYBTq5FlO6DYf2TGVe6Eu.HA6BjuPk+jJeoMd3r.Fp5mTALsvC2kvvd
GHgoMz3rHFF7llVp1zR4i.OOocvL1akxLTtnH1p.cvwVDr2RIkjnuFkXg7+8
00s2Dt+2h1Wj.054SebgVjn9Chdjg1HL8GfVF5G0+Kimv62DciqiqJs3G83g
HamW5FNRTZKm0Bs4DigRVyD3ArNARxj6yTSt8nsAyZi.9dKAeTBbMp0H+d.X
vThhhlZY6ECJkj2hwj1zli7pTquL+I6S.+7XxgvQhDBjfKCJgoOOb0ZUB2Xs
JahEZi2cTqRr+7fwpzMahLwk6Dr3O9G+iK9e+R31WhV7zdSTu1ZRO6MgaOFl
j7iNSgU7EAbnAPGBoaaS.gchPhnmIBuAN26sQIylzElrFPNiQHz2AJY1BZbV
IS5sIwq5aT1e9353zEwa2cLao2G8.p5QOXkLfpjboYFqhTM.2CjL8QLtP2Zr
dNb9avD4MsGoo10xAmHeV65AAR2Uul4OwyQ+iv0q92WcBXLtzeGH0owFVZRB
VLh.ZpjckTPY8veT2tEQkfOwwcfigFqjRDTsZhNyxnCeyv.obpg.IsZkDp3j
ZDX3j7TL4BWWn6HcEr8wOARq0KKFp6i7Ay3H7j+Vd2h0QIg+3uD2UVGc4uk2
GcPOIcXVb511qYTZi0Lp1fEsZofDaW2GuBGN+5NVKVjh4DEtStRyFQy1cS7s
mzXpYKHZeApV.qOr74XyzN6Oz928gkg6103xOz3QLuK9077oP7X0kh2leIR0
k1G803xmmVc0v8ZbHSCBG2m+d46xx1s4mIccz9sGiqHFVVwGJ+AqhrOxFO27
X4yKTkS1PWNSVejjt52xmqBUdwzcQa0ZUcBVVU75nmCOlj84tyr41keR1P2t
vpDR9OuuVw3GV9x930oaMMhVPs4xkUmgVXSLEVyNi8N1FtqiGV+lWCK8T3Ac
m73gmB2adSTn7Jtrvrzzj1EU8bIQOmUT7t3saOAEyR20egViB6u3mR0EtYne
aaIG97ws4k94DSZjbH7qsQ6Ls4lERAZ+y+8vswaByhxhyeEfQUElq.+WNrxj
2Js5u4k70NJYslDuJ5awqy9hshZRFz2d7tRRzxp2xqieI5PV6qkE9xg1W4UB
lzW53SECR+bVzlcI5dQ6an0lNQyQjMkW155mH2zJUnZzVmshdEQdFwj8Ikif
sJ8An774GU9Yqmq4LgmzPpEjgZTPogSm1xi2tN56UFw9P4LKExQtPTKuSOVX
CMLt.4qJRR9blmGWv8hKvXvEvi3xa.axr6bLF1D3G1jOQsV5tzU9A0Z0feqv
UF0jjPBiYhXtMMoJV0t3AFpp5Eco2H.KdWT0BnWhFMnQGDzdri7ns+MXG6ZR
.iYM14TF.6f9wN1jhc2.tDsvOR4JxfPmEK38KaqCrnVsHial6Y9Pa6xTd2fz
gzi6WU1iJ4xKZ2B0SvmEusRKwOUIG1beN8NZzMBGaCFxyB5D0H.WQhRHa5ZE
fqsBXJaEXWaE3orUPbsUPlpVwXHmcSKpG4ZkB0yP2Jim17ibgUUUYoMVc2ha
km+PdJ9qz+w3Ot7uofVY7e0bI1m6ywaMF7Fct0IPQcosaNop9d3UsF8ObgHS
swagqiq8xeoJGMVRBXExtjsPADjRhn4eSeoW2dKdRn7QkLvjcU5uPwXZ92HH
jYUT28ShafOs9n88Ft8kByEE017T3Ihzco6qrcNfnZ8bGyRq5vlxqJqxN9SW
0tepZc61jz7XCh5d8OVWyakuJRZVMcQzq3Sc5B8yRqBWsRW8sdeIwLPXfZgD
jfkhvTLJ607jldR3SVeIvTHjbh6ney3gkEaR2ldXmwMEWQO0Y5UaFMHkFOgo
o1RITPnY.gzw.vnjnMmVsBIRA1mRqTGFj4s.BXVLMudnXqGUIwJJwNhWHsdk
z7MLFv+jM12UIbsG2qwQfHPVRqDK3jbTV+9BqdmHF30q3n4QFyiLd2Lxn32n
7GXow0pq+btaj+bXV193mNlkqaVy3DLJ2c9RR5SgIENyrZf2P99r1AoenVoQ
eE4qMwqWmD4kPe0ZeB0ji.EKwS.Kr1+225pi+yVru30Q4Tprg9xr5BcNzWMv
Q8Xyp0h8EF4KXNxWyQ9ZNxWyQ9ZNxWyQ9ZNxWyQ958UjunusQ9hZVjm4.3b3
ulC+0b3ulC+0b3ulC+0b3ulC+0b3ulcx+rS9mC+07Hi4QFyg+5MI7W6WX7l7
9IdYuIT5I2UHlYqMRprN9b3UCFz8NfAxmw8aTcbWC6mBjUG2MmoKRuAA8KLK
7uZV2z2vyHSs9e18M3AWQiztiIG7SXL4n3bGZinyAkaNnbyAkyY2y1d6unqM
CBi3sEOuOcyBzGgEYo5+pdWgvWAjhvsieU46hU3bmWOPnUXixes2UwdSq0c0
DYXg52sAf6tLTRs.WPo06F3l8bbGhmD9sNdR+mM24h7Cd0dy4o2AeJs5TDNh
Xbejcu5QfH06OlCAZ8GhS7O6fFGGf4JpwD7wAZX06WPSq6D.LvZv+3.M46VP
CyyS6fwgW72Z7RqtV0dseqcbe+Df7br6w9+hqvZ9VtUUHiG.RuMJc7FjXKEI
cAm+lmWKSSj0w2CQV20nWZasSUHTwpwzJlpvIaDl6dqXpBstQDo6shohWXjp
3Vn0gotU3RZFfUScqvkTtnj.McsBmDWvmxzOw0FAaNYGlS1g4jcXNYGlCo6b
HcmS1g4QFyiLlS1g2zjcXT6xsWbxNvB3HrPRdrXaeVp0N3ra.tpoNiG1OxU5
7k08wHNxr8dSMCXkTUc1PL3Qqpza899NmN9xgjElypiE+A7XQfVgXmTcLDbM
G6lZZAXN2M0zBAcvzDgWAM8Fr9o6HIceztnsqWTN+waNtAHDI+H5lMHnIviD
ztjzt4v2Ls1K3Lx6jClhCgYG2WuB1CPtRhzLmxQWXhFJz+wLknRzGpPG84VA
YB1k067javqxf.JKPnkAyrTF8zxBr.qXmamlGvnkS8g2weMJaQXRxXy6rVCk
XAXfS4pg2FFv3FRhA5qD3vGdWX3DPjRp1FF.TG+.meeX.5YiXvqai8W.zd19
Nln+GTvpxL8LDH7jedScPSf9CvDO.BS3AbSZaZ59ZQtBk1JIQUz85s6O8mQz
0BKmdTnEKnolbki.5EG72Ymzgj300pr90vZkn+OfOVCFeh726GLpOCkXi8LT
5ra1KsjxfIxJoL.1hQfZLhY.srMNVaOs4boW85m2EoLhaxgyT6I+O48x9Wd5
S7+90qYfKXt1P3SwbRySSF8DQZXO9o3j3rezDzZq1gA+c8kj4HmSBTyV5i70
UnSujjuOzDAjb87tLIRBiSSDOdvENjlH3O9x9zi6V1Ee6LGSe9WeEDQTsYK.
LvdbIwTk5qz5HR57PcS8U.0Eouxzmg9GN8Ev0rLDZ0+apyhXXak5YsV76McV
.kVnHB35gNiSokd1809cpRKsoAiQoEPbyUZA+VozRSQMXJpRTiiJsbBHe8Js
.x6CkVXSnRKMwbBhXwbJ8pTZwYwgdPkkpMkl2SNOQBx.JVXcwzYzXAguIZr.
2QZr.RfTqwBULRMVZgzBEDPvJNCtbEVP2.EV.uovRqtuRRBnTL0HP3L5qfX+
z4iEkVaWpBoP7ypsBh+SqKVzJpnERKsg58bJqfT2bkUf2HkUZIkwPZFoxJsw
XNQKlALqmlKUUE39PUE5zopRaDWolXUUZKHDnAXs95lkF1kpoB9ciyUzF4gL
oOyXzT4FDjmeIZcb3h+R3SKRLqv3ElkD8hUZELLKY2ZYM2b8UH1sdArRy1vX
CCCqbJVPB.BXHhgeRz7SgTwr5oHUuVOGWHn2DMEQ2QZJJjVJIUSRKgdm8pUM
GukNhDqKfIX43UTjvmd8DQ9zwV0Pf65IR+IwqVLskqbjvj0ZlSLb2TS7mq.w
0VPu6ZIdycn0aiBhbpLW3hcKJvcWX0.SuVsBI2E5DNYJDxYXSL1XlTOkR3Mf
Y+60pFx5vnqUUvahhfkaDHc8hYSR3SezpDzgOt663OgqUa+qwQeytet7J3J8
4m0xVamnwUc67cJm06CeodGPorqrJId0uk8E8DOu7klW+UalJsK3qutfmdwr
89z5Jo6WmukDgFdFrdz.fKMlTXoP5gZ4THqRAL44reSyIJbTf.AleEoco820
iedNgpx5fv8uTrvqL40b0RraYeu7Bzu02El4sL0bT7F16TdCmntTdChnucNG
3dh3P5f3Hu6IN72oDGlVc.kRIExwRb.EBEn.MuA7Cwg1AwQb2SbDuSINDI2X
YIlgGMwQXRvEl.i7jDGVGDG9cOwQ9Nk3fY1op3lWQij3X1VDKWyL9f3v6f3v
t6INp2oDmB+RNRNCCPUanZ9fyH5fyPu24L.d1dJ8bBWp8TbpJfwUBD9h4MRT
G7FxcOugLaO0X4MMsmxGDGnChCtwtLy8IwgNaO0HINsrmxGDmt7fCb2SbXy1
SMVhSS6o7AwoKO3ft6IN7Y6oFKwoo8T9f3zgGb.0cOwQ791dpQxYZZOkO3Lc
37F3t2cwfb1dJ8bBWp8TLkHfJvbF+x4Mc36F3t2awfZ1dpwxaZYOEJe89Y2j
OtPhSGNvA326SRgQy1SMRhCHUpZ0h8.wQ1Awg0XON89j3.y1SMVhSS6o7wTU
pNHNz6dhCd1dpwRbZZOkGHNpN7YrcYKeeSbHuysmBcw1S4CNSGtK1rgcdeqW
Le1bJ8TBWr4TTV.QvXzKOrlhtbcCbuSaDyVSMVZSSqo7AuoK22b26qX4rwTi
j2zJ3T9f2zg6at68TrZ1TpwRaZYJkGnMc37F4ce.FPyVRMVdSKKo7.uoCe2H
t64Mv6aCoFIkokgTdfxzgWat6SpX1rcTKjWpYTTEIPKwgRu7nYJ5H0It6SnX
5rUTijzzzHJevZ5HSst6SoXxrMTii0zxDJevZ5vSe28ITLd1DpQxZZZAkOXM
ckG528oMwrATij0zz9IOvZ3cEBy6bVy6ZamjizzIb4F2jOHKcDKAjOIK1en1
mu14bmSOhZKXPu5nok05.xsmykVy95c44R6qXotVSTWpIpWpIpC0TyC+3Kul
vtTS75C95Kul.GpoSdYtId8tz3sYUYnCu1s.RNKvr.OAlhFnZcwpmuZ3GbUM
chvEPB7.H09DQumZhSZdvT+JPxrAuUldTRDK..IVZ24jjhNJ3JawJWZw.B4A
vwoZBTCxfr86pSpONM.SnbadsqMBHfWu4QWVxU1lkN0lwC0lwHtc6nzdzens
4HPo+pxjBc.Sy1q1DIKK3Jawtv0AOH4g6BzPU4mD7WWMQboKwk9nS4hPNNxG
0DxEwoBeTStfdXOTQLWFfSQCN91bnmUdX4o+L.iPRkvrIBVmyn0W22ST3TO.
HsmjqVGwqqtcY7jZPoiRIqBj3RsZjxxifQJoiBdS5AZch6F8v2f5FgbG9f.l
VlB0NwKlzQAdm74hjalOjxwbQj.wGpmxbQQX1fSepU6oVeHJyHdfS31CTzNK
v6rZpSrZb2r5qjRPbkRbsywxbwNBkrkhq9pS5RUyfIQlqS1z3io6YtLcO0KC
tcohX9vzSkqSXANM1t8LVb2lwBl9t.fUNKepUev3xF1TNgK0YUvu520NYUA2
G0D3pCM7tNDtU0fyd3PILqHWpdRoS7xQcAdmQfZMbqGAZzg4y.tVUaAOf.JA
mbx7s0EbsuucQv3I5LdRKtksABV.WQsM3l5yUe8qr8RTNfvfOlxf3jJs9vBQ
hKpYPvtp6bSkz5959l16TG.vroPGMhKpuvmD0WbppIvTnzlK.tOnlXWl3wZP
N3az0opFSmBNE1Ie13EoLXlqdr9pqIWLjhKlhAJtU0Sh3ArSxVGbBYEmGfJO
OIT7pySBLRqfIm.RiBF8VfjgKOn..ofDfKO.AJu909Z0EslndQV.xcn7ppHP
3BegNrlfMcZjQCEd4A9MCwCjJjjqFn.yYiDAwY1yU4lQMq759dHha8YPfmBM
ucrxIngMl7DDWfDDqt2ThIXYZ6vflE36Q5mhM8LggvYVCfTLyAICiJLaWp4m
QH0W6pI4tHSzGil3toHqOB7NvbO5W8FgQHfoPLgMZcZ4nz7QjsDdVWv01fIN
0hGdBBLvCvZRiInhFCcjZCcDF48MCkbcAWcS1EmlMbCtQ6hhwAZfL2ktcWf2
Go5RO.OEJh.XoKlOh8xrXXmF2gwdotbxAQXuLF2Is4p58WYc4lkkCJTGiob8
7O100fFtUAbACqLoGLAPAHjjffAKAPr.kdVLj3jjFnQIWcGEMlN5UVWKalAZ
8H.g6qZB4nyZ59kW07t5oELmZfBxicbsqscBN4UIu3f0Syvl9pKlWpK2xeFu
vpbRglpd+UVWtYft7L10oLgRFraiLsF8q0xH.oHDIcvRZJW3j7exaxEbZtxp
d5UVWtMbUNEd6IuxOuic42vN5j3PB6oAsCUteFm3xrJ9QCDjZLop2UVWtM7G
bUq.kPXVhrBhY0enMuOPIH.kMPARlYoRREl7SokJA0Eb0cR7X5jWYc4DOYRx
6J2pa.4tc6Bt98DgPAqghDywPo0AO0W26ioQivyCWWM4hiw7T8bNgwcXkT9p
QHb2tuFs+PwcaqikaB+0TKRKdz9Oi2l+OI1+49HypRI+9o1qDte0WhyhVkcb
e95i36E6xsKMKRj8aOFW7ZS269PwwG6Iq.h5kVwwjrXsxh4KlByI6Yjl4Tcf
ypqnmBKJydqkDhl.W8O1Oxex76eczyg5GoMZ9zKqRSx6dZpY9hoQo+igbl+M
iqjgFqjDyQDr8Y9b7VCzE0dg3T7Qym3oWdNNIopddnp10+XEmWqKeYe3535y
5ayosZUyBEfUH6IBLJffTRDM+a5K0tsU7TP4iIYf4HCR+EpVDZ92HHjcMx7p
mB2.CZ8Q88Et8k72CXAp7b90rzZR2ktu53eMfnpt+iYoUcrRoO4rfxSZ7x2U
Zd5ujtMbU5xRRZ2DfSe2i56ce9Q28eKJII8akmTrcSABWsRWEsvaIlY1TlQA
BIXTRT2aYJlYxjluWadRoa7Ti4lzFh5oNv2LioVrIca5gcgqhFaOvoW8sYYf
TJwl6z33tBRFCHjSF.DkDs4zpSHQJ6dCZfDgvlMBcSMS.t7zgBsdLkDqnD6H
MgjwD4eCiA7uSGy4hDj1i2z3DPDHKIShEbRNJpeWXN1Z+c6vuusAi.FhgQgy
L2Yl68JyU+L+qO7+Csz5s3.
-----------end_max5_patcher-----------

Assignment 4 – Matthew Xie

For assignment 4, I decided to utilize the fft object and create an audio effect patch that would mimic the sound of recent favorite music genre ‘Vaporwave’.

I created a noise reduction subpatch. Furthermore, a degrading fft subpatch is also used and linked to the output, playing along with the other signal. After these two subpatches, the audio signal is then run through the original patch where it is stretched out in real time (slowed down). This is done by using the delay effect.

I also added another simple visual presentation, that is very similar to the one we made in class. A japanese city pop song was used in demonstration, to achieve that ‘vaporwave aesthetic’.

Another demo: https://soundcloud.com/thewx/assignment4-demo/s-K8iMc

 

Top level patch:

Noise Reduction Patch:

Degrading Patch

Visual Patch:

Assignment 4 – Kun Peng

Frequency Visualization

This project is based on what we did in class – visualizing audio using pfft~. I parsed pfft output into four bands using bin index. Each band covers a range of frequency(low, mid-low, mid-high, high, respectively), represented by blue, green, pink and white. This video shows the visualization of Morton Gould’s Interplay: IV. Very Fast, With Verve and Gusto, a piece with very beautiful orchestration. Piano, which dominants most part of the music, lies in green and blue bands while woodwind, brass, and percussions occasionally pop up in pink and white. I also tried to run the patch with pop music, in which there seems to be a larger pink/white presence.

The video quality seems to be embarrassingly bad… I will work on it next time…

The Patch is similar to the class one, with additions of more matrices in the main patch and band filters in pfft~ subpatch. Currently the bin filters are hard coded, I’ll see if I can improve the model to adjust bin filters on the fly.

subpatch