Plugin Boutique has launched an exclusive sale on the HERSE Max for Live device by K-Devices, offering over 70% off on the sound design tool designed to rearrange and process audio. Looking for an effect to inject life in your beats? A companion to work with during your guitar performances? Something to enrich your vocals, […]
Ableton has announced a sale on the recently updated Ableton Live 10, upgrades and Packs, offering a 25% discount for the next few days only. From now until Tuesday, June 11th, save 25% on all Ableton software. This offer applies to new purchases of Ableton Live 10 Suite, Standard and Intro, upgrades to Ableton Live […]
It’s all about voltage these days. Ableton’s new CV Tools are designed for integrating with modular and semi-modular/desktop gear with CV. And they’re built in Max – meaning builders can learn from these tools and build their own.
The basic idea of CV Tools, like any software-CV integration, is to use your computer as an additional source of modulation and control. You route analog signal directly to your audio interface – you’ll need an interface that has DC coupled outputs (more about that separately). But once you do that, you can make your software and hardware rigs work together, and use your computer’s visual interface and open-ended possibilities to do still more stuff with analog gear.
This is coming on the eve of Superbooth, and certainly a lot of the audience will be people with modular racks. But nowadays, hardware with CV I/O is hardly limited to Eurorack – gear from the likes of Moog, Arturia, KORG, and others also makes sense with CV.
CV Tools aren’t the first Max for Live tools for Ableton Live – not by far. Spektro Audio makes the free CV Toolkit Mini, for instance. Its main advantage is a single, integrated interface – and a clever patch bay. There’s a more extensive version available for US$19.99.
Ableton’s own CV Tools is news, though, in that these modules are powerful, flexible, and polished, and have a very Ableton-esque UI. They also come from a collaboration with Skinnerbox, the live performance-oriented gearheads here in Berlin, so I have no doubt they’ll be useful. (Yep, that’s them in the video.) I think there’s no reason not to grab this and Spektro and go to town.
And since these are built in Max, Max patchers may want to take a look inside – to mod or use as the basis of your own.
What you get:
CV Instrument lets you treat outboard modular/analog gear as if it’s integrated with Live as a plug-in.
Trigger drums and rhythms with CV Triggers.
CV Utility is a signal processing hub inside Live.
CV Instrument, with complements existing Ableton devices for integrating outboard MIDI instruments and effects with your projects in Live
CV Triggers for sequencing drum modules
CV Utility for adding automation curves, add/shift/multiple signals, and other processing tools
CV Clock In and CV Clock Out for clocking Live from outboard analog gear and visa versa
CV In which connects outboard analog signal directly to modulation of parameters inside Live
CV Shaper, CV Envelope Follower, and CV LFO which gives you graphical tools for designing modulation inside Live and using it for CV control of your analog hardware
And there’s more: the Rotating Rhythm Generator, which lets you dial up polyrhythms. This one works with both MIDI and CV, so you can work with either kind of external hardware.
I got to chat with Skinnerbox, and there’s even more here than may be immediately obvious.
For one thing, you get what they tell us is “extremely accurate broad-range” auto calibration of oscillators, filters, and so on. That’s often an issue with analog equipment, especially once you start getting complex or adding polyphony (or creating polyphony by mixing your software instruments with your hardware). Here’s a quick demo:
Clocking they say is “jitter free” and “super high resolution.”
So this means you can make a monster hybrid combining your computer running Ableton Live (and all your software) with hardware, without having to have the clock be all over the place or everything out of tune. (Well, unless that’s what you’re going for!)
If you’re in Berlin, Skinnerbox will play live with the rig this Friday at Superbooth.
They sent us this quick demo of working with the calibration tools, resulting in an accurate ten-octave range (here with oscillator from Endorphin.es).
To interface with their gear, they’re using the Expert Sleepers ES8 interface in the modular. You could also use a DC-coupled audio interface, though – MOTU audio interfaces are a popular choice, since they’ve got a huge range of interfaces with DC coupling across various interface configurations.
CV Tools is listed as “coming soon,” but a beta version is available now.
For full CV control of analog gear, you’ll want a DC-coupled audio interface. Most audio interfaces lack that feature – I’m writing an explanation of this in a separate story – but if you do have one with compatible outputs, you’ll be able to take full advantage of the features here, including tuned pitch control. MOTU have probably made more interfaces that work than anyone else. You can also look to a dedicated interface like the Expert Sleepers one Skinnerbox used in the video above.
See MOTU and Expert Sleepers, both of which Skinnerbox have tested:
Universal Audio have already written to say they’ll be demoing DC coupling on their audio interfaces at Superbooth with Ableton’s CV Tools, so their stuff works, too. (Double-checking which models they’re using.)
But wait – just because you lack the hardware doesn’t mean you can’t use some of the functionality here with other audio interfaces. Skinnerbox remind us that any audio interface inputs will work with CV In in Pitch mode. Clock in and out will work with any device, too.
Max 8 – and by extension the latest Max for Live – offers some serious powers to build your own sonic and visual stuff. So let’s tune in some videos to learn more.
The major revolution in Max 8 – and a reason to look again at Max even if you’ve lapsed for some years – is really MC. It’s “multichannel,” so it has significance in things like multichannel speaker arrays and spatial audio. But even that doesn’t do it justice. By transforming the architecture of how Max treats multiple, well, things, you get a freedom in sketching new sonic and instrumental ideas that’s unprecedented in almost any environment. (SuperCollider’s bus and instance system is capable of some feats, for example, but it isn’t as broad or intuitive as this.)
The best way to have a look at that is via a video from Ableton Loop, where the creators of the tech talk through how it works and why it’s significant.
In this presentation, Cycling ’74’s CEO and founder David Zicarelli and Content Specialist Tom Hall introduce us to MC – a new multi-channel audio programming system in Max 8.
MC unlocks immense sonic complexity with simple patching. David and Tom demonstrate techniques for generating rich and interesting soundscapes that they discovered during MC’s development. The video presentation touches on the psychoacoustics behind our recognition of multiple sources in an audio stream, and demonstrates how to use these insights in both musical and sound design work.
The patches aren’t all ready for download (hmm, some cleanup work being done?), but watch this space.
If that’s got you in the learning mood, there are now a number of great video tutorials up for Max 8 to get you started. (That said, I also recommend the newly expanded documentation in Max 8 for more at-your-own-pace learning, though this is nice for some feature highlights.)
dude837 has an aptly-titled “delicious” tutorial series covering both musical and visual techniques – and the dude abides, skipping directly to the coolest sound stuff and best eye candy.
Yes to all of these:
There’s a more step-by-step set of tutorials by dearjohnreed (including the basics of installation, so really hand-holding from step one):
Suffice to say that also could mean some interesting creations running inside Ableton Live.
It’s not a tutorial, but on the visual side, Vizzie is also a major breakthrough in the software:
That’s a lot of looking at screens, so let’s close out with some musical inspiration – and a reminder of why doing this learning can pay off later. Here’s Second Woman, favorite of mine, at LA’s excellent Bl__K Noise series:
Isotonik Studios has announced availability of Sempler Pro, a sample sequence manipulator by Noiss COKO designed to create complex patterns by performing simple actions. The whole device is exclusively driven by its integrated sequencer, which among other parameters allows to set a different starting point, size, pitch, level and delay amount for every single step. […]
It’s the season of the wavetable – again. With Ableton Live 10.1 on the horizon and its free Wavetable device, we’ve got yet another free Max for Live device for making sound materials – and this time, you can make your wavetables from images.
Let’s catch you up first.
Ableton Live 10.1 will bring Wavetable as a new instrument to Standard and Suite editions – arguably one of the bigger native synth editions to Live in its history, ranking with the likes of Operator. And sure, as when Operator came out, you already have plug-ins that do the same; Ableton’s pitch is as always their unique approach to UI (love it or hate it), and integration with the host, and … having it right in the box:
Earlier this week, we saw one free device that makes wavetables for you, built as a Max for Live device. (Odds are anyone able to run this will have a copy of Live with Wavetable in it, since it targets 10.1, but it also exports to other tools). Wave Weld focuses on dialing in the sounds you need and spitting out precise, algorithmic results:
One thing Wave Weld cannot do, however, is make a wavetable out of a picture of a cat.
For that, you want Image2Wavetable. The name says it all: it generates wavetable samples from image data.
This means if you’re handy with graphics software, or graphics code like Processing, you can also make visual patterns that generate interesting wavetables. It reminds me of my happy hours and hours spent using U+I Software’s ground-breaking MetaSynth, which employs some similar concepts to build an entire sound laboratory around graphic tools. (It’s still worth a spin today if you’ve got a Mac; among other things, it is evidently responsible for those sweeping digital sounds in the original Matrix film, I’m told.)
Image2Wavetable is new, the creation of Dillon Bastan and Carlo Cattano – and there are some rough edges, so be patient and it sounds like they’re ready to hear some feedback on how it works.
But the workflow is really simple: drag and drop image, drag and drop resulting wavetable into the Wavetable instrument.
Okay, I suspect I know what I’m doing for the rest of the night.
Wavetables are capable of a vast array of sounds. But just dumping arbitrary audio content into a wavetable is unlikely to get the results you want. And that’s why Wave Weld looks invaluable: it makes it easy to generate useful wavetables, in an add-on that’s free for Max for Live.
Ableton Live users are going to want their own wavetable maker very soon. Live 10.1 will add Wavetable, a new synth based on the technique. See our previous preview:
Live 10.1 is in public beta now, and will be free to all Live 10 users soon.
So long as you have Max for Live to run it, Wave Weld will be useful to other synths, as well – including the developer’s own Wave Junction.
Because wavetables are periodic by their very nature, it’s more likely helpful to generate content algorithmically than just dump sample content of your own. (Nothing against the latter – it’s definitely fun – but you may soon find yourself limited by the results.)
Wave Wend handles generating those materials for you, as well as exporting them in the format you need.
1. Make the wavetable: use waveshaping controls to dial in the sound materials you want.
2. Build up a library: adapt existing content or collect your own custom creations.
3. Export in the format you need: adjusting the size les you support Live 10.1’s own device or other hardware and plug-ins.
The waveshaping features are really the cool part:
Unique waveshaping controls to generate custom wavetables
Sine waveshape phase shift and curve shape controls
Additive style synthesis via choice of twenty four sine waveshape harmonics for both positive and negative phase angles
Saw waveshape curve sharpen and partial controls
Pulse waveshape width, phase shift, curve smooth and curve sharpen controls
Triangle waveshape phase shift, curve smooth and curve sharpen controls
Random waveshape quantization, curve smooth and thinning controls
Wave Weld isn’t really intended as a synth, but one advantage of it being an M4L device is, you can easily preview sounds as you work.
The download is free with a sign-up for their mailing list.
They’ve got a bunch of walkthrough videos to get you started, too:
Major kudos to Phelan Kane of Meta Function for this release. (Phelan is an Ableton Certified Trainer as well as a specialist in Reaktor and Maschine on the Native Instruments side, as well as London chairman for AES.)
I’m also interested in other ways to go about this – SuperCollider code, anyone?
Plugin Boutique has announced a Sonic Faction Valentines Sale, offering a 30% discount on its inspiring and creative range of Max for Live devices and Kontakt instruments. The sale includes popular products such as Tricky Traps, Whoosh Machine and Dope Matrix: Mod Squad for Max for Live, the Archetype Kontakt Bundle and the Futurism hybrid […]
Instead of just accepting all this machine learning hype, why not put it to the test? Magenta Studio lets you experiment with open source machine learning tools, standalone or inside Ableton Live.
Magenta provides a pretty graspable way to get started with an field of research that can get a bit murky. By giving you easy access to machine learning models for musical patterns, you can generate and modify rhythms and melodies. The team at Google AI first showed Magenta Studio at Ableton’s Loop conference in LA in November, but after some vigorous development, it’s a lot more ready for primetime now, both on Mac and Windows.
I got to sit down with the developers in LA, and also have been playing with the latest builds of Magenta Studio. But let’s back up and first talk about what this means.
Magenta Studio is out now, with more information on the Magenta project and other Google work on musical applications on machine learning:
Artificial Intelligence – well, apologies, I could have fit the letters “ML” into the headline above but no one would know what I was talking about.
Machine learning is a better term. What Magenta and TensorFlow are based on is applying algorithmic analysis to large volumes of data. “TensorFlow” may sound like some kind of stress exercise ball you keep at your desk. But it’s really about creating an engine that can very quickly process lots of tensors – geometric units that can be combined into, for example, artificial neural networks.
Seeing the results of this machine learning in action means having a different way of generating and modifying musical information. It takes the stuff you’ve been doing in music software with tools like grids, and lets you use a mathematical model that’s more sophisticated – and that gives you different results you can hear.
You may know Magenta from its involvement in the NSynth synthesizer —
NSynth uses models to map sounds to other sounds and interpolate between them – it actually applies the techniques we’ll see in this case (for notes/rhythms) to audio itself. Some of the grittier artifacts produced by this process even proved desirable to some users, as they’re something a bit unique – and you can again play around in Ableton Live.
But even if that particular application didn’t impress you – trying to find new instrument timbres – the note/rhythm-based ideas make this effort worth a new look.
Recurrent Neural Networks are a kind of mathematical model that algorithmically loops over and over. We say it’s “learning” in the sense that there are some parallels to very low-level understandings of how neurons work in biology, but this is on a more basic level – running the algorithm repeatedly means that you can predict sequences more and more effectively given a particular data set.
Magenta’s “musical” library applies a set of learning principles to musical note data. That means it needs a set of data to “train” on – and part of the results you get are based on that training set. Build a model based on a data set of bluegrass melodies, for instance, and you’ll have different outputs from the model than if you started with Gregorian plainchant or Indonesian gamelan.
One reason that it’s cool that Magenta and Magenta Studio are open source is, you’re totally free to dig in and train your own data sets. (That requires a little more knowledge and some time for your computer or a server to churn away, but it also means you shouldn’t judge Magenta Studio on these initial results alone.)
What’s in Magenta Studio
Magenta Studio has a few different tools. Many are based on MusicVAE – a recent research model that looked at how machine learning could be applied to how different melodies relate to one another. Music theorists have looked at melodic and rhythmic transformations for a long time, and very often use mathematical models to make more sophisticated descriptions of how these function. Machine learning lets you work from large sets of data, and then not only make a model, but morph between patterns and even generate new ones – which is why this gets interesting for music software.
Crucially, you don’t have to understand or even much care about the math and analysis going on here – expert mathematicians and amateur musicians alike can hear and judge the results. If you want to read a summary of that MusicVAE research, you can. But it’s a lot better to dive in and see what the results are like first. And now instead of just watching a YouTube demo video or song snippet example, you can play with the tools interactively.
Magenta Studio lets you work with MIDI data, right in your Ableton Live Session View. You’ll make new clips – sometimes starting from existing clips you input – and the device will spit out the results as MIDI you can use to control instruments and drum racks. There’s also a slide called “Temperature” which determines how the model is sampled mathematically. It’s not quite like adjusting randomness – hence they chose this new name – but it will give you some control over how predictable or unpredictable the results will be (if you also accept that the relationship may not be entirely linear). And you can choose number of variations, and length in bars.
The data these tools were trained on represents millions of melodies and rhythms. That is, they’ve chosen a dataset that will give you fairly generic, vanilla results – in the context of Western music, of course. (And Live’s interface is fairly set up with expectations about what a drum kit is, and with melodies around a 12-tone equal tempered piano, so this fits that interface… not to mention, arguably there’s some cultural affinity for that standardization itself and the whole idea of making this sort of machine learning model, but I digress.)
Here are your options:
Generate: This makes a new melody or rhythm with no input required – it’s the equivalent of rolling the dice (erm, machine learning style, so very much not random) and hearing what you get.
Continue: This is actually a bit closer to what Magenta Studio’s research was meant to do – punch in the beginning of a pattern, and it will fill in where it predicts that pattern could go next. It means you can take a single clip and finish it – or generate a bunch of variations/continuations of an idea quickly.
Interpolate: Instead of one clip, use two clips and merge/morph between them.
Groove: Adjust timing and velocity to “humanize” a clip to a particular feel. This is possibly the most interesting of the lot, because it’s a bit more focused – and immediately solves a problem that software hasn’t solved terribly well in the past. Since the data set is focused on 15 hours of real drummers, the results here sound more musically specific. And you get a “humanize” that’s (arguably) closer to what your ears would expect to hear than the crude percentage-based templates of the past. And yes, it makes quantized recordings sound more interesting.
Drumify: Same dataset as Groove, but this creates a new clip based on the groove of the input. It’s … sort of like if Band-in-a-Box rhythms weren’t awful, basically. (Apologies to the developers of Band-in-a-Box.) So it works well for percussion that ‘accompanies’ an input.
So, is it useful?
It may seem un-human or un-musical to use any kind of machine learning in software. But from the moment you pick up an instrument, or read notation, you’re working with a model of music. And that model will impact how you play and think.
More to the point with something like Magenta is, do you really get musically useful results?
Groove to me is really interesting. It effectively means you can make less rigid groove quantization, because instead of some fixed variations applied to a grid, you get a much more sophisticated model that adapts based on input. And with different training sets, you could get different grooves. Drumify is also compelling for the same reason.
Generate is also fun, though even in the case of Continue, the issue is that these tools don’t particularly solve a problem so much as they do give you a fun way of thwarting your own intentions. That is, much like using the I Ching (see John Cage, others) or a randomize function (see… all of us, with a plug-in or two), you can break out of your usual habits and create some surprise even if you’re alone in a studio or some other work environment.
One simple issue here is that a model of a sequence is not a complete model of music. Even monophonic music can deal with weight, expression, timbre. Yes, theoretically you can apply each of those elements as new dimensions and feed them into machine learning models, but – let’s take chant music, for example. Composers were working with less quantifiable elements as they worked, too, like the meaning and sound of the text, positions in the liturgy, multi-layered quotes and references to other compositions. And that’s the simplest case – music from punk to techno to piano sonatas will challenge these models in Magenta.
I bring this up not because I want to dismiss the Magenta project – on the contrary, if you’re aware of these things, having a musical game like this is even more fun.
The moment you begin using Magenta Studio, you’re already extending some of the statistical prowess of the machine learning engine with your own human input. You’re choosing which results you like. You’re adding instrumentation. You’re adjusting the Temperature slider using your ear – when in fact there’s often no real mathematical indication of where it “should” be set.
And that means that hackers digging into these models could also produce new results. People are still finding new applications for quantize functions, which haven’t changed since the 1980s. With tools like Magenta, we get a whole new slew of mathematical techniques to apply to music. Changing a dataset or making minor modifications to these plug-ins could yield very different results.
And for that matter, even if you play with Magenta Studio for a weekend, then get bored and return to practicing your own music, even that’s a benefit.
Where this could go next
There are lots of people out there selling you “AI” solutions and – yeah, of course, with this much buzz, a lot of it is snake oil. But that’s not the experience you have talking to the Magenta team, partly because they’re engaged in pure research. That puts them in line with the history of pure technical inquiries past, like the team at Bell Labs (with Max Mathews) that first created computer synthesis. Magenta is open, but also open-ended.
As Jesse Engel tells CDM:
We’re a research group (not a Google product group), which means that Magenta Studio is not static and has a lot more interesting models are probably on the way.
Our goal is just for someone to come away with an understanding that this is an avenue we’ve created to close the gap between our ongoing research and actual music making, because feedback is important to our research.
Isotonik Studios has announced the release of Signal by Chaos Culture, a set of Max for Live building blocks that allows you to build your own signal flow that can be used to create audio, control voltage or just modulate anything in Live. With Signal, Chaos Culture has created a system that lets you quickly […]