18-090, Fall 2019

Final – Beat Maker

sebastir@andrew.cmu.edu — Mon, 09 Dec 2019 14:30:49 +0000

In this Project, I wanted to make something to make beat making easier. I used a keyboard linked with some audio libraries, and adjusted velocity based on pitch (with variable tempo). I also used live.grid to create a 16 beat sequencer on 3 tracks.

mwiedman – Final Project

mwiedman@andrew.cmu.edu — Mon, 09 Dec 2019 14:22:51 +0000

For my final project, I wanted to work with manipulating visuals since it’s something I focused a lot on working with audio in the class. My original idea was to use leap motion to manipulate videos – with the idea that electronic artists would be able to do something more engaging than stand at a laptop during their concerts. Instead you could see their hands move to change the graphics on the screen – almost like a conductor of the visuals.

However, I really struggled to get leap motion to work on my laptop so I had to change tactics. I started using the pitch of the audio to automatically control certain aspects of the jitter object – ranging from color to position to shape. If I were going to keep working on this project I think I would like to explore with adding more colors and working with the jit.gl.multiple object. I would also like to focus on manipulating the audio during the song that is playing, and then having the manipulated sound also affect the audio. This way the artists could still manipulate the video based on the effects they add to the song.

I used my assignment 4 patch for my started file as this project, because I liked the way that the audio of an fft controlled a jitter matrix. This also gave me a good foundation to look at what parameters I could modify

https://drive.google.com/drive/u/1/folders/1yKQAsIA8H_8AN7JkZjUtSC-zTUlDngxd

ejhicks – Project 2: Color Chords

ejhicks@andrew.cmu.edu — Mon, 09 Dec 2019 14:13:53 +0000

For my second project, I was inspired by the idea of using color as a means of producing music (or, at least, the illusion of music). Videos like Colored Virtual Piano (https://www.youtube.com/watch?v=8FcexZUTITc) encouraged me to examine the possibility of creating a program that could analyze the colors in front of it and create a soundscape based upon what it could interpret.

Originally, my plan was to create a functioning keyboard, where each note was associated with a single point on a grid, and the placement of a color would reproduce that note. However, while working on the project and discovering that MAX had the tendency to read all colors before it, rather than simply isolating colors in live feeds, I was inspired to alter my program to allow for a shifting soundscape, where moving colors produced a sequence of notes and chords based on horizontal position and variety of color.

As such, I was fortunate enough to discover a patcher designed by Matt Westerwick which could associate a table’s output with a distinct chord or piano note. With this asset, I could design the program to detect one of three colors (RGB), assign its position in the video to a set of coordinates which would be assigned to a unique position in a table, and then translate the tabular position to a shifting series of notes based on horizontal position.

The project heavily employs the findbounds function to detect (and then pack into a table) the coordinates of the colors (as mentioned above) relative to the left, right, top, and bottom of the video input. When experimentation proved that stagnant colors would quickly create unpleasant loops of sound, the change function was employed in order to filter out repetitions of input from said stagnant colors.

Upon final review of the project, I wish I had discovered a means of more clearly differentiating the sound output between Red and Blue; I wished for them both to be piano-based outputs, but sometimes this caused the sound output to lack unique qualities when comparing the colors. However, the soundscape is still an interesting canvas to explore with this project, and I am quite satisfied with the final result.

An screenshot of the project’s primary code is below, and the link to the google drive is as follows: https://drive.google.com/drive/u/1/folders/1L8qZdDVdyAyvA-vile3aCzIXV5FNDoZ5.

jcrisafu – Project 2 – Player Vocoder

jcrisafu@andrew.cmu.edu — Mon, 09 Dec 2019 14:02:52 +0000

The sounds of a vocoder have always fascinated me. From Laurie Anderson’s ominous voice in O Superman to the funky robot fun of Stevie Wonder and Daft Punk’s discographies, the vocoder has an intense amount of potential within itself. With this project, I decided to explore how this uniquely electronic method could extend into other fields by allowing a vocoder to play itself through MIDI information, as well as see how different source sounds other than a voice could react with a vocoder style.

The foundations behind a vocoder. The two fftins~ are your two audio sources, the second one usually a saw wave for robotic goodness.

In this presentational version of the patch, I decided to combine the four string parts of Ravel’s String Quartet in F Major, because I can. As of right now, I am only able to use MIDI 0 type files running concurrently with each other, as the parsing of channels from a MIDI 1 file became incredibly daunting when trying to keep the patch self-contained, as opposed to working in conjunction with a DAW (in my case, GarageBand. Sad.). I allow for two different source audio sources; either an ADC~ input, or another file through SFPlay~. This allows for both the classic talk-box style, as well as the ability to turn other pieces of pre-recorded music or speech to be transformed. As a test, I used Shintaro Sakamoto’s “A Stick and Slacks” for its rhythmic intrigue and staccato nature to interplay with the legato phrases of Ravel.

This is that. That’s this. (As a note, the noise~ is used to make consonants more pronounced by exploiting the clipping that would occur when speaking into a microphone.)

I believe that this patch could become an interesting live performance technique, especially with single-voice instruments like strings, woodwinds, and brass. The opportunity for someone to create a multitude of voices from one source opens up fascinating opportunities for self-duets, trios, and more. I would have loved to find more flexibility in affecting the MIDI data outside of creating my own MIDI files that were set in stone.

https://drive.google.com/drive/u/1/folders/1yoklE-qoguK9-JydRIqeqbp0AHKOYa3Z


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eludwick – Project 2 – LEAP Audio Effect Suite

eludwick@andrew.cmu.edu — Mon, 09 Dec 2019 13:42:13 +0000

I made this patch with the intention of creating a set of audio effects that could be incorporated into some form of sound, whether mp3 or live, that could be mostly controlled by LEAP using hand gestures.

In its final form, the patch I made controls reverb, a multi-voiced vocoder, and an LFO that controls the amount of pitch bend the incoming audio receives and how fast it shifts. The patch is slightly finicky in that you need to activate the LEAP data in all the sub-patches before audio will come through. Parts of the sub-patches are patches I found online or in tutorials, but all the LEAP data tracking is my own. I also decided to use Luis Fonsi’s Despacito since we used that in class several times.

When first opened, the patch contains two different input options, a hand tracking toggle, and access to the sub-patches that contain the individual effects. The mp3 is by far easier to work with. The adc~ works, but not as effectively as I would have liked.

Once you decide the input and hit the desired effect’s number key, you can open up the corresponding sub-patch.

The reverb patch is fairly straight-forward. It uses the reverb patch found in max > help > examples. The hand gestures directly effect the basic parameters of a reverb effect. The most noticeable are the Decay and Size, while the Diffusion and Hi Frequency Cutoff are more subtle.

The vocoder is names after Gir from Invader Zim. The dry/wet part of the patch is from – https://www.youtube.com/watch?v=mi9CjZxk8zs and the vocoder effect is from – https://www.youtube.com/watch?v=4feOFLX6238. I used these because both were easily controlled by the LEAP data, while other pre-made versions required the mouse to control the various parameters.

Lastly, is the LFO device. The base effect of this is loosely based on this video – https://www.youtube.com/watch?v=uyzY_ZP54pA. However, I altered it in order to get a different effect. I was trying to replicate an effect I had heard from a soundtrack, but I ended up getting more of a whammy bar/warbly effect.

Overall, I am very happy with this. It is very fun to use, and can be very easily modded to control different effects or to add new ones. I am planning on continuing to work and develop this because I think it could eventually turn into a very useful tool, and I think this is a very good point to be at for the first iteration.

https://drive.google.com/open?id=1xMT-od471FLCn6pOWAYY9XWCGeTdMlIO

Le Final Project SaS – shambhav

shambhav@andrew.cmu.edu — Mon, 09 Dec 2019 07:14:05 +0000

Collaborators: Sara Frankel + Shambhavi Mishra

This project in collaboration with Sara is an audio visualization and manipulation max patch that uses a leap motion sensor as its main controlling factor. Our project was divided into two parts, the audio and the visual manipulation.

Sara took charge in creating the audio component while I worked with the visual component.

The visual patch originally used jit.gl.plato and jit.gl.multiple in order to create a spectrum of shapes that could be modified in sub patches via position, scale, rotation, and color. The overall shape could then be modified by the user.

Original Patch

However, we realized that this visual component would be hard to control with a leap motion sensor, therefore we modified the visual to be one large entity that was controlled by the palm position of the hand detected by the leap motion sensor rather than individual shapes. Therefore, the world looked more unified.

New Visual

With a more manageable jit.world, we then applied the position, rotation, and scale parameters of a jit.gl.multiple object to our overall object (jit.gl.plato). We also wanted the audio component to interact with the visual component, therefore we used part of my project one to convert audio signal frequencies into pitch and then color. This connection allowed for the visual shapes to reflect the frequencies of the audio files being played through color.

Visual sub patch

Visual connected to audio main patch

Along with the leap motion, when the user moves the visual around, (up/down/left/right/front/back), the audio track is modified accordingly. Additionally, the more wet signal added, the more fluctuations you can see in the visuals. Below is a picture of how all parts of this project work together.

Final Project in presentation view

For more about the audio aspect of this project check out Sara’s project page: https://courses.ideate.cmu.edu/18-090/f2019/2019/12/09/le-final-project-sas-sfrankel/

Project File Google Drive:

https://drive.google.com/open?id=1oA_ceh31OFaaENqMv01eiZvMfMDXyf6_

Embedded Code:

Audio + Video 


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-----------end_max5_patcher-----------




Video


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-----------end_max5_patcher-----------




Leap Motion

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Le Final Project SaS – sfrankel

sfrankel@andrew.cmu.edu — Mon, 09 Dec 2019 06:47:52 +0000

For the final project of this class, I knew I wanted to incorporate a more tangible quality to bring a new dimension to the not as tangible Max interface. I mean this in the sense that instead of just clicking buttons and letting objects run, I really wanted to use my hands in real time to manipulate what the output of my computer. For this project, I turned to the Leap Motion Sensor for inspiration.

For the starting point of this project, I used the object munger~ to help change parameters ranching from grain to stereo spread. With this patch, I essentially created a form of a theremin in the sense that inputting the data of the position of my hands from the leap motion sensor changed the parameters of the munger~ object.

Here is an image of my starting patch:

Using the parameters that the Leapmotion object intakes, one can use their hand or fingers to manipulate the properties of the grain and the stereo spread. There is a more tangible aspect to this project by incorporating the Leapmotion sensor, making the project more engaging and visually capable to follow from an audience point of view.

I sliced off specific parameters using “zl slice”(i.e. palm position) and connected them to the munger~ object to help connect my two patches together.

At this point, I felt that bringing even more senses to this project would be quite interesting. This is where I collaborated with my colleague Shambhavi Mishra. Shambhavi expressed to me early on that she was very interested in manipulating the output of her computer visually with her hands. We felt that our projects would mesh well as together they bring new dimensions of sense to each others. My project works on pitch and spatialization while hers works with pitch and colors, both being manipulated by the tangible parameters of ones hand position.

Here is an image of the unlocked patch:

To hear more about my partners work, please visit her post:

Le Final Project SaS – shambhav

Link to zip file of work:

https://drive.google.com/drive/folders/1OVeXAEY9rtdWzBFQb9uGcJyH7-CI8mgA?usp=sharing

Compressed Code:

Main Patcher


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k+1k+eLHPJeF
-----------end_max5_patcher-----------




Visual Patcher


----------begin_max5_patcher----------
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43vR06IxQrw+63+SXA3E6
-----------end_max5_patcher-----------




Leap Motion Patcher 

----------begin_max5_patcher----------
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-----------end_max5_patcher-----------

mychang — Final Project

mychang@andrew.cmu.edu — Mon, 09 Dec 2019 06:36:10 +0000

I created my final project using the Leap Motion Controller and machine learning. The sensor will take in the data from my hand movements, read them as different gestures and convert them into digital numbers that the patcher can understand. Each different gesture will output into a different piano chord. The ending position of the hand will also rotate sections of the cubes on the screen.

I downloaded an external helper patch for the leap motion controller from Masayuki Akamatsu.

Link to my google drive folder.

Davidcoo – Project 2: Leap Motion Granular Synth

davidcoo@andrew.cmu.edu — Mon, 09 Dec 2019 06:23:41 +0000

In my project I created a granular synthesizer that is controlled using the leap motion. I started by using a base of the Sugar Synth that we used in class and built on that to be able to control it with using leap motion controls. By utilizing the built in detection of the leap motion, the user is able to control which value they are controlling by doing gestures with their hands (Open hand, fist and the OK symbol), Then they use their other hand to control the value by moving left and right to assign a value to the parameter they have chosen. There is a toggle to pick which hand that is controlling the value and which is controlling the parameter. The parameters that can be controlled are the speed, pitch rate, random pitch, grain size, and number of grains.

Drive Link: https://drive.google.com/drive/u/1/folders/1Zz5Ca0h4jl3yKpqmj89UUT3WMRukfpj2

In my project I used the Sugar Synth: http://formantbros.jp/sako/download.html

I also used the leap motion for max and built on the leap motion made in class.

samuelgo – Project 2: F8R

samuelgo@andrew.cmu.edu — Mon, 09 Dec 2019 06:18:02 +0000

For this project I developed an interactive performance system powered by Max.

The basic premise of the patch is to capture and playback gestural input. Max outputs these gestures as MIDI CC data, which are then converted to CV signals that control a hardware synthesizer.

Three Max objects play a major role in this patch:

mira.frame – The graphical interface for gestural input is designed in a mira.frame object. The mira.frame object mirrors the interface on an iPad connected to the computer running Max over WiFi.
mira.multitouch – The mira.multitouch object allows us to collect multitouch information from the iPad hosting the mira.frame interface. Touch state and y-position are the key information collected in this patch.
mtr – The mtr object, wrapped with some custom logic, records and plays back the gestural input data from the mira.multitouch object.

The core engine in this patch can be extended or augmented to support many types of gestural input. In this implementation the graphical interface consists of 8 faders whose values can be set or automated.

The embedded video demonstrates the patch with a live performance.

Project Resources: https://drive.google.com/drive/u/0/folders/1htNu8UGfB6_NB_QtNnzEGnrOOXTfRYm2