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Andrew Benson

Machine Learning has long been a part of computer music, but with recent advances in the field we have been interested to see how these new tools could be put to use in Max. We invited Isaac Io Schankler to develop an example of their explorations with the 

object that implements the RAVE model in Max. We hope this offers a good starting point for experimenting with ML tools in Max.

There are lots of ways to use machine learning in music! If you are Google or OpenAI, you can spend millions of dollars to scrape the internet for data and train your models using thousands of GPUs. But even if you are not a tech conglomerate with endless resources and questionable ethics, there are ways to make use of machine learning at home that are slightly less resource-intensive and less fraught. Lately I’ve been having fun using Antoine Caillon and Philippe Esling’s 

 (Realtime Audio Variational autoEncoder). You can use RAVE as a kind of “timbre transfer” tool to make one thing sound like another, e.g. make a guitar sound like a violin, or make an orchestra sound like a Game Boy, or yes, make one person’s voice sound like another person.

ML-Screenshot.png

For this patch, I trained a model on the 

, which features recordings by Kinga Augustyn, Ray Chen, Oliver Colbentson, Ko Donghwi, John Garner, Karen Gomyo, Minji Kim, Silei Li, and Emil Telmanyi. (While there are no laws about using copyrighted material to train AI models yet, I tried to stick to recordings that were in the public domain or had similarly permissive licenses.)

If you want to explore further, there are a few other pre-trained models 

. If you’re interested in training your own model, you’ll need at least 3 hours of recorded audio and a computer with a capable GPU. If, like me, you don’t have access to a fancy GPU, you can use a cloud computing service like Google Colab or vast.ai. A Google Colab sketch, helpfully provided by 

. After you run the patch and turn the audio on, you can try out the timbre transfer by turning on the mic input, or by playing back the little synth guitar loop that I provided. You should start to hear violin-like sounds that mimic the audio input—that’s the pre-trained RAVE model trying to reproduce your sounds!

You can then adjust the mix of the original input and the violin models (there are 2) to your liking. I also added some reverb to “soften” the noisy output you sometimes get from RAVE, but you can adjust that too if you like.

You might also want to adjust the delay of the original audio input. It takes RAVE a bit of time to generate its audio, so if you want the violin models to be in sync with the audio input, you will probably have to delay the original signal a bit (usually between 250 and 1000 ms).

Okay, so far so good. But here’s where things get really interesting. To generate its audio, RAVE uses a bunch of constantly changing control parameters. Normally these parameters are controlled directly by the audio input, but we can hijack these parameters and control them manually if we want. RAVE gives us 16 of those parameters to play with. These parameters are created by RAVE during training, so they don’t really map onto the musical parameters that we know and love (e.g. high and low, loud and soft, etc.). But imo that’s part of the fun of it, the exploration and experimentation and noodling to try and locate the kinds of sounds you want!

Since 16 parameters is a lot to deal with, I also added some LFOs that slowly sweep through the range of each parameter, if you just want to hear how the sound changes over time.

9499B_web_72ppi copy.jpg

You’ll need to download and install nn~ first, and then download the patch and supporting materials. After you run the patch and turn the audio on, you can try out the timbre transfer by turning on the mic input, or by playing back the little synth guitar loop that I provided. You should start to hear violin-like sounds that mimic the audio input—that’s the pre-trained RAVE model trying to reproduce your sounds!

timbre-transfer-with-machine-learning-by-isaac-io-schankler

Timbre Transfer with Machine Learning by Isaac Io Schankler

Drums and rhythm are a foundational element of electronic music especially, and every artist has their preferences in how they should sound. Drum voices can also be a fun sound design challenge for Max patching. For this community project, we invited four artists to each create their unique take on some classic percussion sounds - rimshot, clap, cowbell, and cymbal - along with a custom sequencer that puts this collection into action.

 first Collaborative Drum Kit project here.

sequencer-screenshot.png

nouserid-photo.jpg

"I always enjoy making music more when I'm not totally sure what's going to come out of the sequencers next. This sequencer has the ability to generate sequences with semi - predictable variation using just a few parameters.

An initial trigger starts a cascade of possible patterns from the input of the matrix. The matrix basically tells the sequencer its possible destinations after the current step, except for position 0 which is instantly triggered when the sequence restarts. You can also set a delay time for each step to wait before triggering (0 being no delay, 1 being a 16th note, and 16 being 1 bar, etc.). There is also a control for the probability of the delay of a step being applied or ignored. Step size is the note duration and it works on the same time system as the delay.

We also have the optional function to mute (choke) all other voices with each trigger, which can create some interesting variation and unexpected results on its own.

This is a basic implementation of the concept but there are so many different directions you could take it and features you could add, depending on your tastes.." - nouserid. Find 

Note: The sequencer patch download includes all of the patches listed below.

no.pinball_plusLabels.maxzip

takuma.jpg

"Mesh is a physical modeling cymbal synthesizer, implementing a 2D waveguide mesh as its resonator with downsampling at the end." - babumamusic. Find 

Cymbal.zip

Loveless_headshot_portrait.jpg

"This patch is inspired by the Roland 808 cowbell. I researched and reviewed how others were doing this, like reviewing old circuit diagrams and watching how others were recreating this sound in Ableton. It was a fun exercise." - melodycodes. Find 

Loveless_collabdrumkit_cowbell.maxpat

Z_photo (CYCLING 74 FINAL HEADSHOT).png

"rim_shot uses shaped noise, an envelope, a minimal feedback delay line with modulated params, and an optional chorus effect to produce a sound resembling a synthesized rim shot and other unusual percussive elements.” - onokio. Find 

rim_shot.maxpat

PP.Mjulev.jpg

"I would like to introduce you to my interpretation of a clap synthesizer. The entire module is inspired by the 808 clap and is divided into two voices. You can independently modify the "Punch" and "Release" with the patch. I like to build the instrument into a clear interface as well, as this usually determines how quickly I can generate and create sounds. Have fun trying it out!" - Mjulev. Find 

TheEightClap.maxpat

collaborative-drum-kit-in-max-part-2

Collaborative Drum Kit in Max, Part 2

How do you get started when you begin a project in Max? We asked 3 artists working with Max to share each of their personal starting points. The results are each a unique view into Max…

 This patch offers a starting point for world-building through camera movement and path animation. Here, we layer different camera scenes within one jit.gl.node. The rigged camera has three "look at" modes: (1) facing the direction of movement, (2) looking at the target (blue cube), and (3) looking at the center of the scene (purple sphere). Additionally, this patch utilizes quaternions to calculate rotational movement around the path, producing the yellow spiral. Feel free to play around with variables!

alsoknownasrox.JPG

Starting Point - Roxanne Harris.maxpat

 This patch demonstrates some of the approaches I’ve been exploring using Max in tandem with game engine simulations, inspired in large part by cybernetic systems and their application to organizing sound and sonic events. Here, we see Max communicating with a simulation made with Unreal Engine via OSC to create a feedback control loop: objects in 3D space send information about their movement, location, and collisions to Max to generate MIDI information, and Max sends control data back to the simulation based on this information to prompt changes in the 3D environment. Rather than viewing this arrangement as a kind of data sonification, I’m more excited about this dynamic system as a way of generating complex and evolving sound gestures from relatively simple conditions. Hopefully this can provide a generative starting place for your own sounds and systems, as well!

Matthew D Gantt2_photo credit Adam Ninyo.jpg

startingPoint_MDG.maxpat

Matthew has been kind enough to share the 

Unreal Engine project file for this Starting Point

, in addition to the pre-compiled binaries. The project file is large! Almost 2GB. It should open in UE 5.11, which you can download via the 

. The binaries were compiled on late versions of both Mac OS and Windows. Neither Matthew nor Cycling ‘74 can provide tech support in the event your system does not play nice with any of these files.

 My work focuses on researching traditional Japanese music,and through this research, I have identified three essential elements that I hypothesize are very important: pitch, time, and timbre👺

The patches I created allow for a highly organic approach to these elements🌿

Specifically, the "time" patch enables users to freely divide a range of time and generate rhythms⏱️

while the "note" patch creates heterophony based on a single fundamental melody🎼

The "synth" patch features two 2-operator FM synthesizers with the ability to organically change timbre at specific moments🎹

By using the "all" patch, all of these functions can be integrated, supporting the creation of rich, organic music🌯

I view Max8 as a versatile notebook that allows users to quickly test and explore fragmented ideas🗒️

Although it might take some time to master, Max8 offers powerful support when pursuing a specific approach or concept📈

While the patches I've created may seem complex, I would be delighted if they inspire even one more person to explore the possibilities of Max🤝

私は日本の伝統音楽の研究をしており、その研究によって非常に重要だと仮説を立てた3つの要素：音程、時間、音色に対して、非常に有機的なアプローチを可能にするパッチを制作しました🌿

具体的には、ある時間の範囲を自由に区切り、リズムを生成できる「time」⏱️

一つの基本メロディから、ヘテロフォニーを生成する「note」🎼

そして、2つの2オペレーターFMシンセサイザーに、特定の時間で音色が有機的に変化する機能を搭載した「synth」です🎹

これらをまとめた「All」パッチによって、全ての機能を連携させ、非常に有機的な音楽を作るためのアイデアをサポートします🌯

Max8は、断片的なアイデアを非常に高速に試すことができるノートブックのようなものだと考えています🗒️

習得には時間がかかるかもしれませんが、追求したいアプローチがある時に、非常に強力なサポートをしています📈

このパッチは少し複雑かもしれませんが、Maxを使ってみたいと考える人が一人でも増えたらとても嬉しいです🤝

Get the Latest on Max and our Community

Timbre Transfer with Machine Learning by Isaac Io Schankler

Collaborative Drum Kit in Max, Part 2

Starting Points in Max pt. 2

An Evening with Max and RNBO in Brooklyn

3 Explorations in Gen~

One Button Patching Challenge

RNBO and gen~

RNBO - Everything You Need to Know, All in One Place

Generating Sound and Organizing Time: An Interview with Graham Wakefield and Gregory Taylor

Collaborative Drum Kit in Max