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

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.

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

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:

Link to zip file of work:

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

Compressed Code:

Main Patcher

<pre><code>
----------begin_max5_patcher----------
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-----------end_max5_patcher-----------
</code></pre>



Visual Patcher

<pre><code>
----------begin_max5_patcher----------
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43vR06IxQrw+63+SXA3E6
-----------end_max5_patcher-----------
</code></pre>



Leap Motion Patcher 
<pre><code>
----------begin_max5_patcher----------
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</code></pre>

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

Link to my google drive folder.

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:

1. 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.
2. 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.
3. 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

The beginning of the patch is a color tracker that the user can interact with. The user clicks inside the pwindows to choose the colors they want to track and the color data and location found using jit.findbounds is sent into the bottom of the patch.

I used the bottom of the image received from jit.findbounds as my control for pitch. I explored the groove object and controlling samples and I put that in this project to control not only the pitch but the delay and gain of a sample. While the bottom location controls pitch the rgb values control delay and gain. Initially, I also controlled feedback but when playing around with the comb object I found it gave more interesting results when I kept feedback high and changed gain and delay. Red and blue control delay while green controls gain. Below are examples of the difference using stems from a band named Pomplamoose.

Another aspect of the project is that the sound is binaural using the top right of pictures to control the amplitude and phase of a cycle to control the path of the sound. Initially, I had the top right be where the sound existed in the soundscape but I thought it’d be more interesting if the sound was moving through space instead of being still since it is a still image.

The last example that I didn’t use a drawing to show that since it’s a color tracker it can be used both with images and moving pictures. So for this example, I used stock sounds of nature as my sample and a picture of my cat and Kirby plush that I moved around as my controls.

https://drive.google.com/drive/folders/1HrYdWD5CCZ6iBj7FTXnzaYILSPrvPsi2?usp=sharing

Many times, I find that people don’t know that conducting an ensemble in the marching arts is very different from conducting a wind ensemble group or conducting an orchestra. Drum majors are often called the “time-keepers” of a marching band or corps. The hardest part of their job is having to deal with the physics of sound given the marching arts’ natural environment, the football field. On top of having to ignore sounds that bounce off the concrete in stadiums or the delays coming from the performing members who are facing the opposite direction, drum majors have to make sure their conducting patterns are consistent, precise, and extremely clear.

This is what inspired me to create this project. I wanted to create a tool that allows beginner conductors to analyze their patterns to help them on the field. For a lot of high school students who are just starting to learn the basics and foundations of conducting a marching band, they have tendencies to rush or slow down certain beats of their patterns. For example, in a simple 4/4 pattern, because of the different lengths of the pathways, a natural tendency for beginners is to be slow on beat 3 and rush into beat 4.

The tool that I created consists of two visuals: one shows where the metronome hits (shown in red), and the other is where the conductor’s beats hit (shown in blue).

I started by coding a metronome. At first, I used an impulse signal but ran into problems when I realized not all the impulses were shown in the visual display because the length of the impulse signal was too short. So to create the metronome click, I recorded the sound of a pen hitting against glass and edited the length using audacity.

For the second display wave, I used a contact microphone to show where the conductor’s beats were landing. This microphone can be connected to a music stand.

From there, all the user has to do is set a tempo they want to conduct at and hit the record button to record their conducting patterns. The recording is displayed on the two different visuals where the conductor can analyze if their beats are consistent or not and figure out how they can fix it.

Here is the link to the patch:

https://drive.google.com/open?id=1HrdEWJYiKBX41kkMyY01yWA7dxYtgG9J

and hoped that I could accomplish something similar to this one. So I started out trying to build just one object (like a sphere) and tried to manipulate its size and color as the music plays. But I struggled with making the object as complicated as the one I show in the video.

So I changed my mind and tried to do something that is more achievable for me. After following this tutorial

to build a particle system, I tried to rebuild the patch so that the particle system can react to music. I also added color features into my patch – I can change the background color of my world, and change the brightness of my particles so that the particle system won’t look too boring. Users can adjust the amplitude of the particle system and the size of the system to achieve different effects. To demonstrate that, I made the presets to show the different visualizations my system can achieve through just changing numbers in some number boxes.

Here is a video I recorded that is me demonstrating the patch:

And here is the link to the google drive.

In my case, I planned to convert water movement into music. Specifically, I decided to manipulate data about a form of water that we all are familiar with: rain. By using Node.js via Max, I was able to retrieve weather data from the MetaWeather API. I chose to take in numbers from four major cities: Seoul, New York, London, and Brasilia. Even though there was a variety of interesting data, I decided to only use each cities’ current weather state from this API.

Along with retrieving weather conditions, I set up four micro servos using two Arduinos in the ceiling of our Media Lab. Also, I placed a black rectangular container filled with water, approximately three meters below these servos. The servos centered perpendicular to center points of nonexistent four sub-rectangles of the container. With this system, I used my weather data to rotate the motors of servos for dropping water into the container. By doing so, the droplets caused water movement and a webcam recognized those movements to trigger musical notes. I not only used data from a specific form of water but also implemented a system where physical movements of water will make sound signals.

Following is the process of making music in this setup. At first, I used Max to convert weather status data into integers that I assigned. These numbers will control how fast the micro servos move in order to drop water into the container. As servos finish letting go of water droplets, a webcam set to view the water surface of the container will read in changing water wave movement as the drops splash into the container. The video from the webcam is manipulated so that four sub-rectangles each correspond to different musical notes. Also, within those four matrices, five rows of matrices were once again divided so that rows from the left to right corresponds to each notes’ -2 octave up to +2 octave, respectively.

There are a few important components of this project.

• Attaching a funnel (narrow side blocked) as a carrier of water onto a servo
• Having light shine onto the water surface in the container
• Running two Arduinos in order to use four servos (one Arduino supports only two servos)
• Using a black container as it is effective for Max to recognize any movements that happen in a webcam’s frame
• Implementing variations in musical notes corresponding to water movement

With this system, a never-ending music can be made by water from rain (water) data. Compared to music that we listen on a daily basis, this water music can sound boring. However, if we think about it running for more than a few days, then one musical note created by a drop of water every five minutes is truly meaningful. Below are the screenshots of the main patches:

One of the most difficult parts of this project was building the container to hold water. I used black acrylic plates and cut sidewalls using a table saw from TechSpark. With the parts cut, I glued them using acrylic cement onto a plate that worked as a floor. Finally, I guaranteed the container to be watertight by applying silicon onto the sides of the container’s interior.

Overall, I really enjoyed how I could use a very fundamental element to make music. As much as I now understand why it is difficult to deal with water and electronics, I believe that water is a great source of inspiration for the field of music. There will be a broader spectrum to the usage of water when more people realize that water can be utilized for creative works. For that reason, I would love to continue exploring ways to incorporate water with art and music.

Link to this project’s Google Doc: https://drive.google.com/open?id=172NFpCFe8TwA5Eb65xX9gccARMKjXd-N