VCV Rack nears 1.0, new features, as software modular matures

VCV Rack, the open source platform for software modular, keeps blossoming. If what you were waiting for was more maturity and stability and integration, the current pipeline looks promising. Here’s a breakdown.

Even with other software modulars on the scene, Rack stands out. Its model is unique – build a free, open source platform, and then build the business on adding commercial modules, supporting both the platform maker (VCV) and third parties (the module makers). That has opened up some new possibilities: a mixed module ecosystem of free and paid stuff, support for ports of open source hardware to software (Music Thing Modular, Mutable Instruments), robust Linux support (which other Eurorack-emulation tools currently lack), and a particular community ethos.

Of course, the trade-off with Rack 0.xx is that the software has been fairly experimental. Versions 1.0 and 2.0 are now in the pipeline, though, and they promise a more refined interface, greater performance, a more stable roadmap, and more integration with conventional DAWs.

New for end users

VCV founder and lead developer Andrew Belt has been teasing out what’s coming in 1.0 (and 2.0) online.

Here’s an overview:

  • Polyphony, polyphonic cables, polyphonic MIDI support and MPE
  • Multithreading and hardware acceleration
  • Tooltips, manual data entry, and right-click menus to more information on modules
  • Virtual CV to MIDI and direct MIDI mapping
  • 2.0 version coming with fully-integrated DAW plug-in

More on that:

Polyphony and polyphonic cables. The big one – you can now use polyphonic modules and even polyphonic patching. Here’s an explanation:

https://community.vcvrack.com/t/how-polyphonic-cables-will-work-in-rack-v1/

New modules will help you manage this.

Polyphonic MIDI and MPE. Yep, native MPE support. We’ve seen this in some competing platforms, so great to see here.

Multithreading. Rack will now use multiple cores on your CPU more efficiently. There’s also a new DSP framework that adds CPU acceleration (which helps efficiency for polyphony, for example). (See the developer section below.)

Oversampling for better audio quality. Users can set higher settings in the engine to reduce aliasing.

Tooltips and manual value entry. Get more feedback from the UI and precise control. You can also right-click to open other stuff – links to developer’s website, manual (yes!), source code (for those that have it readily available), or factory presets.

Core CV-MIDI. Send virtual CV to outboard gear as MIDI CC, gate, note data. This also integrates with the new polyphonic features. But even better –

Map MIDI directly. The MIDI map module lets you map parameters without having to patch through another module. A lot of software has been pretty literal with the modular metaphor, so this is a welcome change.

And that’s just what’s been announced. 1.0 is imminent, in the coming months, but 2.0 is coming, as well…

Rack 2.0 and VCV for DAWs. After 1.0, 2.0 isn’t far behind. “Shortly after” 2.0 is released, a DAW plug-in will be launched as a paid add-on, with support for “multiple instances, DAW automation with parameter labels, offline rendering, MIDI input, DAW transport, and multi-channel audio.”

These plans aren’t totally set yet, but a price around a hundred bucks and multiple ins and outs are also planned. (Multiple I/O also means some interesting integrations will be possible with Eurorack or other analog systems, for software/hardware hybrids.)

VCV Bridge is already deprecated, and will be removed from Rack 2.0. Bridge was effectively a stopgap for allowing crude audio and MIDI integration with DAWs. The planned plug-in sounds more like what users want.

Rack 2.0 itself will still be free and open source software, under the same license. The good thing about the plug-in is, it’s another way to support VCV’s work and pay the bills for the developer.

New for developers

Rack v1 is under a BSD license – proper free and open source software. There’s even a mission statement that deals with this.

Rack v1 will bring a new, stabilized API – meaning you will need to do some work to port your modules. It’s not a difficult process, though – and I think part of Rack’s appeal is the friendly API and SDK from VCV.

https://vcvrack.com/manual/Migrate1.html

You’ll also be able to take advantage of an SSE wrapper (simd.hpp) to take advantage of accelerated code on desktop CPUs, without hard coding manual calls to hardware that could break your plug-ins in the future. This also theoretically opens up future support for other platforms – like NEON or AVX acceleration. (It does seem like ARM platforms are the future, after all.)

Plus check this port for adding polyphony to your stuff.

And in other Rack news…

Also worth mentioning:

While the Facebook group is still active and a place where a lot of people share work, there’s a new dedicated forum. That does things Facebook doesn’t allow, like efficient search, structured sections in chronological order so it’s easy to find answers, and generally not being part of a giant, evil, destructive platform.

https://community.vcvrack.com/

It’s powered by open source forum software Discourse.

For a bunch of newly free add-ons, check out the wonder XFX stuff (I paid for at least one of these, and would do again if they add more commercial stuff):

http://blamsoft.com/vcv-rack/

Vult is a favorite of mine, and there’s a great review this week, with 79 demo patches too:

There’s also a new version of Mutable Instruments Tides, Tidal Modular 2, available in the Audible Instruments Preview add-on – and 80% of your money goes to charity.

https://vcvrack.com/AudibleInstruments.html#preview

And oh yeah, remember that in the fall Rack already added support for hosting VST plugins, with VST Host. It will even work inside the forthcoming plugin, so you can host plugins inside a plugin.

https://vcvrack.com/Host.html

Here it is with the awesome d16 stuff, another of my addictions:

Great stuff. I’m looking forward to some quality patching time.

http://vcvrack.com/

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Why is this Valentine’s song made by an AI app so awful?

Do you hate AI as a buzzword? Do you despise the millennial whoop? Do you cringe every time Valentine’s Day arrives? Well – get ready for all those things you hate in one place. But hang in there – there’s a moral to this story.

Now, really, the song is bad. Like laugh-out-loud bad. Here’s iOS app Amadeus Code “composing” a song for Valentine’s Day, which says love much in the way a half-melted milk chocolate heart does, but – well, I’ll let you listen, millennial pop cliches and all:

Fortunately this comes after yesterday’s quite stimulating ideas from a Google research team – proof that you might actually use machine learning for stuff you want, like improved groove quantization and rhythm humanization. In case you missed that:

Magenta Studio lets you use AI tools for inspiration in Ableton Live

Now, as a trained composer / musicologist, I do find this sort of exercise fascinating. And on reflection, I think the failure of this app tells us a lot – not just about machines, but about humans. Here’s what I mean.

Amadeus Code is an interesting idea – a “songwriting assistant” powered by machine learning, delivered as an app. And it seems machine learning could generate, for example, smarter auto accompaniment tools or harmonizers. Traditionally, those technologies have been driven by rigid heuristics that sound “off” to our ears, because they aren’t able to adequately follow harmonic changes in the way a human would. Machine learning could – well, theoretically, with the right dataset and interpretation – make those tools work more effectively. (I won’t re-hash an explanation of neural network machine learning, since I got into that in yesterday’s article on Magenta Studio.)

https://amadeuscode.com/

You might well find some usefulness from Amadeus, too.

This particular example does not sound useful, though. It sounds soulless and horrible.

Okay, so what happened here? Music theory at least cheers me up even when Valentine’s Day brings me down. Here’s what the developers sent CDM in a pre-packaged press release:

We wanted to create a song with a specific singer in mind, and for this demo, it was Taylor Swift. With that in mind, here are the parameters we set in the app.

Bpm set to slow to create a pop ballad
To give the verses a rhythmic feel, the note length settings were set to “short” and also since her vocals have great presence below C, the note range was also set from low~mid range.
For the chorus, to give contrast to the rhythmic verses, the note lengths were set longer and a wider note range was set to give a dynamic range overall.

After re-generating a few ideas in the app, the midi file was exported and handed to an arranger who made the track.

Wait – Taylor Swift is there just how, you say?

Taylor’s vocal range is somewhere in the range of C#3-G5. The key of the song created with Amadeus Code was raised a half step in order to accommodate this range making the song F3-D5.

From the exported midi, 90% of the topline was used. The rest of the 10% was edited by the human arranger/producer: The bass and harmony files are 100% from the AC midi files.

Now, first – these results are really impressive. I don’t think traditional melodic models – theoretical and mathematical in nature – are capable of generating anything like this. They’ll tend to fit melodic material into a continuous line, and as a result will come out fairly featureless.

No, what’s compelling here is not so much that this sounds like Taylor Swift, or that it sounds like a computer, as it sounds like one of those awful commercial music beds trying to be a faux Taylor Swift song. It’s gotten some of the repetition, some of the basic syncopation, and oh yeah, that awful overused millennial whoop. It sounds like a parody, perhaps because partly it is – the machine learning has repeated the most recognizable cliches from these melodic materials, strung together, and then that was further selected / arranged by humans who did the same. (If the machines had been left alone without as much human intervention, I suspect the results wouldn’t be as good.)

In fact, it picks up Swift’s ticks – some of the funny syncopations and repetitions – but without stringing them together, like watching someone do a bad impression. (That’s still impressive, though, as it does represent one element of learning – if a crude one.)

To understand why this matters, we’re going to have to listen to a real Taylor Swift song. Let’s take this one:i’

Okay, first, the fact that the real Taylor Swift song has words is not a trivial detail. Adding words means adding prosody – so elements like intonation, tone, stress, and rhythm. To the extent those elements have resurfaced as musical elements in the machine learning-generated example, they’ve done so in a way that no longer is attached to meaning.

No amount of analysis, machine or human, can be generative of lyrical prosody for the simple reason that analysis alone doesn’t give you intention and play. A lyricist will make decisions based on past experience and on the desired effect of the song, and because there’s no real right or wrong to how do do that, they can play around with our expectations.

Part of the reason we should stop using AI as a term is that artificial intelligence implies decision making, and these kinds of models can’t make decisions. (I did say “AI” again because it fits into the headline. Or, uh, oops, I did it again. AI lyricists can’t yet hammer “oops” as an interjection or learn the playful setting of that line – again, sorry.)

Now, you can hate the Taylor Swift song if you like. But it’s catchy not because of a predictable set of pop music rules so much as its unpredictability and irregularity – the very things machine learning models of melodic space are trying to remove in order to create smooth interpolations. In fact, most of the melody of “Blank Space” is a repeated tonic note over the chord progression. Repetition and rhythm are also combined into repeated motives – something else these simple melodic models can’t generate, by design. (Well, you’ll hear basic repetition, but making a relationship between repeated motives again will require a human.)

It may sound like I’m dismissing computer analysis. I’m actually saying something more (maybe) radical – I’m saying part of the mistake here is assuming an analytical model will work as a generative model. Not just a machine model – any model.

This mistake is familiar, because almost everyone who has ever studied music theory has made the same mistake. (Theory teachers then have to listen to the results, which are often about as much fun as these AI results.)

Music theory analysis can lead you to a deeper understanding of how music works, and how the mechanical elements of music interrelate. But it’s tough to turn an analytical model into a generative model, because the “generating” process involves decisions based on intention. If the machine learning models sometimes sound like a first year graduate composition student, that may be that the same student is steeped in the analysis but not in the experience of decision making. But that’s important. The machine learning model won’t get better, because while it can keep learning, it can’t really make decisions. It can’t learn from what it’s learned, as you can.

Yes, yes, app developers – I can hear you aren’t sold yet.

For a sense of why this can go deep, let’s turn back to this same Taylor Swift song. The band Imagine Dragons picked it up and did a cover, and, well, the chord progression will sound more familiar than before.

As it happens, in a different live take I heard the lead singer comment (unironically) that he really loves Swift’s melodic writing.

But, oh yeah, even though pop music recycles elements like chord progressions and even groove (there’s the analytic part), the results take on singular personalities (there’s the human-generative side).

“Stand by Me” dispenses with some of the ticks of our current pop age – millennial whoops, I’m looking at you – and at least as well as you can with the English language, hits some emotional meaning of the words in the way they’re set musically. It’s not a mathematical average of a bunch of tunes, either. It’s a reference to a particular song that meant something to its composer and singer, Ben E. King.

This is his voice, not just the emergent results of a model. It’s a singer recalling a spiritual that hit him with those same three words, which sets a particular psalm from the Bible. So yes, drum machines have no soul – at least until we give them one.

“Sure,” you say, “but couldn’t the machine learning eventually learn how to set the words ‘stand by me’ to music”? No, it can’t – because there are too many possibilities for exactly the same words in the same range in the same meter. Think about it: how many ways can you say these three words?

“Stand by me.”

Where do you put the emphasis, the pitch? There’s prosody. What melody do you use? Keep in mind just how different Taylor Swift and Ben E. King were, even with the same harmonic structure. “Stand,” the word, is repeated as a suspension – a dissonant note – above the tonic.

And even those observations still lie in the realm of analysis. The texture of this coming out of someone’s vocal cords, the nuances to their performance – that never happens the same way twice.

Analyzing this will not tell you how to write a song like this. But it will throw light on each decision, make you hear it that much more deeply – which is why we teach analysis, and why we don’t worry that it will rob music of its magic. It means you’ll really listen to this song and what it’s saying, listen to how mournful that song is.

And that’s what a love song really is:

If the sky that we look upon
Should tumble and fall
Or the mountain should crumble to the sea
I won’t cry, I won’t cry
No, I won’t shed a tear
Just as long as you stand
Stand by me

Stand by me.

Now that’s a love song.

So happy Valentine’s Day. And if you’re alone, well – make some music. People singing about hearbreak and longing have gotten us this far – and it seems if a machine does join in, it’ll happen when the machine’s heart can break, too.

PS – let’s give credit to the songwriters, and a gentle reminder that we each have something to sing that only we can:
Singer Ben E. King, Best Known For ‘Stand By Me,’ Dies At 76 [NPR]

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Magenta Studio lets you use AI tools for inspiration in Ableton Live

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.

If you’re working with Ableton Live, you can use Magenta Studio as a set of devices. Because they’re built with Electron (a popular cross-platform JavaScript tool), though, there’s also a standalone version. Developers can dig far deeper into the tools and modify them for your own purposes – and even if you have just a little comfort with the command line, you can also train your own models. (More on that in a bit.)

Side note of interest to developers: this is also a great showcase for doing powerful stuff with machine learning using just JavaScript, applying even GPU acceleration without having to handle a bunch of complex, platform-specific libraries.

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:

g.co/magenta
g.co/magenta/studio

AI?

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 —

https://nsynthsuper.withgoogle.com/

That also has its own Ableton Live device, from a couple years back.

https://magenta.tensorflow.org/nsynth-instrument

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.

Things like more impressive MIDI generation (https://magenta.tensorflow.org/music-transformer – check out “Score Conditioned”)

And state of the art transcription: (https://magenta.tensorflow.org/onsets-frames)

And new controller paradigms:
(https://magenta.tensorflow.org/pianogenie)

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.

So okay, music makers – have at it:

g.co/magenta
g.co/magenta/studio

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Midi Madness 3 algorithmic melody generator on sale for $59.95 USD!

Midi Madness 3 sale 20 off PIB

Plugin Boutique has announced an exclusive sale on the Midi Madness 3 world-class MIDI generator software for Windows and Mac. Midi Madness 3 can create an unlimited number of melodies using a simple set of probability weightings. Simply set some parameters, such as a chord sequence and some MIDI controllers, and let Midi Madness go […]

The post Midi Madness 3 algorithmic melody generator on sale for $59.95 USD! appeared first on rekkerd.org.

zenAud.io releases ALK2 looping software for Windows

zenAudio ALK2 Windows

zenAud.io has released the previously announced Windows version of its critically acclaimed ALK looping software. The Mac version of ALK2 has been a favorite among songwriters and live performers and enjoys an enthusiastic following amongst loop artists all over the world, recognized as “an extremely easy to use looper station that overrides typical limitations, adds […]

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Ableton Live 10.1: more sound shaping, work faster, free update

There’s something about point releases – not the ones with any radical changes, but just the ones that give you a bunch of little stuff you want. That’s Live 10.1; here’s a tour.

Live 10.1 was announced today, but I sat down with the team at Ableton last month and have been working with pre-release software to try some stuff out. Words like “workflow” are always a bit funny to me. We’re talking, of course, mostly music making. The deal with Live 10.1 is, it gives you some new toys on the sound side, and makes mangling sounds more fun on the arrangement side.

Oh, and VST3 plug-ins work now, too. (MOTU’s DP10 also has that in an upcoming build, among others, so look forward to the Spring of VST3 Support.)

Let’s look at those two groups.

Sound tools and toys

User wavetables. Wavetable just got more fun – you can drag and drop samples onto Wavetable’s oscillator now, via the new User bank. You can get some very edgy, glitchy results this way, or if you’re careful with sample selection and sound design, more organic sounds.

This looks compelling.

Here’s how it works: Live splits up your audio snippet into 1024 sample chunks. It then smooths out the results – fading the edges of each table to avoid zero-crossing clicks and pops, and normalizing and minimizing phase differences. You can also tick a box called “Raw” that just slices up the wavetable, for samples that are exactly 1024 samples or a regular periodic multiple of that.

Give me some time and we can whip up some examples of this, but basically you can glitch out, mangle sounds you’ve recorded, carefully construct sounds, or just grab ready-to-use wavetables from other sources.

But it is a whole lot of fun and it suggests Wavetable is an instrument that will grow over time.

Here’s that feature in action:

Delay. Simple Delay and Ping Pong Delay have merged into a single lifeform called … Delay. That finally updates an effect that hasn’t seen love since the last decade. (The original ones will still work for backwards project compatibility, though you won’t see them in a device list when you create a new project – don’t panic.)

At first glance, you might think that’s all that’s here, but in typical Ableton fashion, there are some major updates hidden behind those vanilla, minimalist controls. So now you have Repitch, Fade, and Jump modes. And there’s a Modulation section with rate, filter, and time controls (as found on Echo). Oh, and look at that little infinity sign next to the Feedback control.

Yeah, all of those things are actually huge from a sound design perspective. So since Echo has turned out to be a bit too much for some tasks, I expect we’ll be using Delay a lot. (It’s a bit like that moment when you figure out you really want Simpler and Drum Racks way more than you do Sampler.)

The old delays. Ah, memories…

And the new Delay. Look closely – there are some major new additions in there.

Channel EQ. This is a new EQ with visual feedback and filter curves that adapt across the frequency range – that is, “Low,” “Mid,” and “High” each adjust their curves as you change their controls. Since it has just three controls, that means Channel EQ sits somewhere between the dumbed down EQ Three and the complexity of EQ Eight. But it also means this could be useful as a live performance EQ when you don’t necessarily want a big DJ-style sweep / cut.

Here it is in action:

Arranging

The stuff above is fun, but you obviously don’t need it. Where Live 10.1 might help you actually finish music is in a slew of new arrangement features.

Live 10 felt like a work in progress as far as the Arrange view. I think it immediately made sense to some of us that Ableton were adjusting arrangement tools, and ironing out the difference between, say, moving chunks of audio around and editing automation (drawing all those lovely lines to fade things in and out, for instance).

But it felt like the story there wasn’t totally complete. In fact, the change may have been too subtle – different enough to disturb some existing users, but without a big enough payoff.

So here’s the payoff: Ableton have refined all those subtle Arrange tweaks with user feedback, and added some very cool shape drawing features that let you get creative in this view in a way that isn’t possible with other users.

Fixing “$#(*& augh undo I didn’t want to do that!” Okay, this problem isn’t unique to Live. In every traditional DAW, your mouse cursor does conflicting things in a small amount of space. Maybe you’re trying to move a chunk of audio. Maybe you want to resize it. Maybe you want to fade in and out the edges of the clip. Maybe it’s not the clip you’re trying to edit, but the automation curves around it.

In studio terms, this sounds like one of the following:

[silent, happy clicking, music production getting … erm … produced]

OR ….
$#(*&*%#*% …. Noo errrrrrrrgggggg … GAACK! SDKJJufffff ahhh….

Live 10 added a toggle between automation editing and audio editing modes. For me, I was already doing less of the latter. But 10.1 is dramatically better, thanks to some nearly imperceptible adjustments to the way those clip handles work, because you can more quickly change modes, and because you can zoom more easily. (The zoom part may not immediately seem connected to this, but it’s actually the most important part – because navigating from your larger project length to the bit you’re actually trying to edit is usually where things break down.)

In technical terms, that means the following:

Quick zoom shortcuts. I’ll do a separate story on these, because they’re so vital, but you can now jump to the whole song, details, zoom various heights, and toggle between zoom states via keyboard shortcuts. There are even a couple of MIDI-mappable ones.

Clips in Arrangement have been adjusted. From the release notes: “The visualisation of Arrangement clips has been improved with adjusted clip borders and refinements to the way items are colored.” Honestly, you won’t notice, but ask the person next to you how much you’re grunting / swearing like someone is sticking something pointy into your ribs.

Pitch gestures! You can pitch-zoom Arrangement and MIDI editor with Option or Alt keys – that works well on Apple trackpads and newer PC trackpads. And yeah, this means you don’t have to use Apple Logic Pro just to pinch zoom. Ahem.

The Clip Detail View is clearer, too, with a toggle between automation and modulation clearly visible, and color-coded modulation for everything.

The Arrangement Overview was also adjusted with better color coding and new resizing.

In addition, Ableton have worked a lot with how automation editing functions. New in 10.1:

Enter numerical values. Finally.

Free-hand curves more easily. With grid off, your free-hand, wonky mouse curves now get smoothed into something more logical and with fewer breakpoints – as if you can draw better with the mouse/trackpad than you actually can.

Simplify automation. There’s also a command that simplifies existing recorded automation. Again – finally.

So that fixes a bunch of stuff, and while this is pretty close to what other DAWs do, I actually find Ableton’s implementation to be (at last) quicker and friendlier than most other DAWs. But Ableton kept going and added some more creative ideas.

Insert shapes. Now you have some predefined shapes that you can draw over automation lanes. It’s a bit like having an LFO / modulation, but you can work with it visually – so it’s nice for those who prefer that editing phase as a way do to their composition. Sadly, you can only access these via the mouse menu – I’d love some keyboard shortcuts, please – but it’s still reasonably quick to work with.

Modify curves. Hold down Option/Ctrl and you can change the shape of curves.

Stretch and skew. Reshape envelopes to stretch, skew, stretch time / ripple edit.

Insert Shapes promises loads of fun in the Arrangement – words that have never been uttered before.

Check out those curve drawing and skewing/scaling features in action:

Freeze/Export

You can freeze tracks with sidechains, instead of a stupid dialog box popping up to tell you you can’t, because it would break the space-time continuum or crash the warp core injectors or … no, there’s no earthly reason why you shouldn’t be able to freeze sidechains on a computer.

You can export return and master effects on the actual tracks. I know, I know. You really loved bouncing out stems from Ableton or getting stems to remix and having little bits of effects from all the tracks on separate stems that were just echos, like some weird ghost of whatever it was you were trying to do. And I’m a lazy kid, who for some reason thinks that’s completely illogical since, again, this is a computer and all this material is digital. But yes, for people are soft like me, this will be a welcome feature.

So there you have it. Plus you now get VST3s, which is great, because VST3 … is so much … actually, you know, even I don’t care all that much about that, so let’s just say now you don’t have to check if all your plug-ins will run or not.

Go get it

One final note – Max for Live. 10.0.6 synchronized with Max 8.0.2. See those release notes from Cycling ’74:

https://cycling74.com/forums/max-8-0-2-released

Live 10.1 is keeping pace, with the beta you download now including Max 8.0.3.

Ableton haven’t really “integrated” Max for Live; they’re still separate products. And so that means you probably don’t want perfect lockstep between Max and Live, because that could mean instability on the Live side. It’d be more accurate to say that what Ableton have done is to improve the relationship between Max and Live, so that you don’t have to wait as long for Max improvements to appear in Max for Live.

Live 10.1 is in beta now with a final release coming soon.

Ableton Live 10.1 release notes

And if you own a Live 10.1 license, you can join the beta group:

Beta signup

Live 10.1: User wavetables, new devices and workflow upgrades

Thanks to Ableton for those short videos. More on these features soon.

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Ableton Live 10.1 beta available, adds user wavetables, new devices & workflow upgrades

Ableton Live 10.1

Ableton has announced the forthcoming Live 10.1 update, adding user wavetables, new devices, workflow upgrades and more to the music production software for Windows and Mac. Live 10.1 expands the possibilities for making and shaping sound, as well as improving key features for editing and finalizing music. The new features in Live 10.1 include: User […]

The post Ableton Live 10.1 beta available, adds user wavetables, new devices & workflow upgrades appeared first on rekkerd.org.

DP10 adds clip launching, improved audio editing to MOTU’s DAW

DP10 might just grant two big wishes to DAW power users. One: pull off Ableton Live-style clip launching. Two: give us serious, integrated waveform editing. Here’s why DP10 might get your attention.

A handful of music tools has stood the test of time because the developers have built relationships with users over years and decades. DP is definitely in that category, established in fields like TV and film scoring.

This also means, however, it’s rare for an update to seem like news. DP10 is a potential exception. I haven’t had hands-on time with it yet, but this makes me interested in investing that time.

Bride of Ableton Live?

The big surprise is, MOTU are tackling nonlinear loop triggering, with what they call the Clips window.

The connection to Ableton Live here is obvious; MOTU even drives home the point with a similar gray color scheme, round indicators showing play status, clips grouped into Scenes (as a separate column) horizontally, and into tracks vertically.

And hey, this works for users – all of those decisions are really intuitive.

Here’s where MOTU has an edge on Ableton, though. DP10 adds the obvious – but new – idea of queuing clips in advance. These drop like Tetris pieces into your tracks so you can chain together clips and let them play automatically. The queue is dynamic, meaning you can add and remove those bits at will.

That sounds like a potential revelation. It’s way easier to grok – and more visible – than Live’s Follow Actions. And it frees users from taking their focus of their instruments and other work just to manually trigger clips.

Also, as with Bitwig Studio, MOTU lets you trigger multiple clips both as scenes and as clip groups. (Live is more rigid; the only way to trigger multiple clips in one step is as a complete row.)

I have a lot of questions here that require some real test time. Could MOTU’s non-linear features here pair with their sophisticated marker tools, the functionality that have earned them loyalty with people doing scoring? How do these mesh with the existing DP editing tools, generally – does this feel like a tacked-on new mode, or does it integrate well with DP? And just how good is DP as a live performance tool, if you want to use this for that use case? (Live performance is a demanding thing.)

But MOTU do appear to have a shot to succeed where others haven’t. Cakewalk added clip triggering years ago to SONAR (and a long-defunct tool called Project 5), but it made barely a dent on Live’s meteoric rise and my experience of trying to use it was that it was relatively clunky. That is, I’d normally rather use Live for its workflow and bounce stems to another DAW if I want that. And I suspect that’s not just me – that’s really now the competition.

More audio manipulation

Every major DAW seems locked now in a sort of arms race in detecting beats and stretching audio, as the various developers gradually add new audio mangling algorithms and refine usability features.

So here we go with DP10 – detect beats, stetch audio, adjust tempo, yadda yadda.

Under the hood, most developers are now licensing the algorithms that manipulate audio – MOTU now works with ZTX Pro from zynaptic. But how you then integrate that mathemagical stuff with user interface design is really important, so this is down to implementation.

It’s certainly doubly relevant that MOTU are adding new beat detection and pitch-independent audio stretching in DP10, because of course this is a natural combination for the new Clips View.

More research needed.

Maybe just as welcome, though, is that MOTU have updated the integrated waveform editor in DP. And let’s be honest – even after decades of development, most DAWs have really terrible editors when it comes down to precise work on individual bits of audio. (I cringe every time I open the one in Logic, for instance. Ableton doesn’t really even have waveform editing apart from the limited tools in the main Arrangement view. And even users of something like Pro Tools or Cubase will often jump out to use a dedicated program.)

MOTU say they’ve streamlined and improved their Waveform Editor. And there’s reason to stay in the DAW – in DP10, they’ve integrated all those beat editing and time stretching and pitch correction tools. They’re also promising dynamic editing tools and menus and shortcuts and … yeah, just have to try this one. But those integrated tools and views look great, and – spectral view!

Other improvements

There’s some other cool stuff in DP10:

A new integrated Browser (this will also be familiar to users of Ableton Live and other tools, but it seems nicely implemented)

“VCA Faders” – which let you control multiple tracks with relative volumes, grouping however you like and with full automation support. This looks ilke a really intuitive way to mix.

VST3 support – yep, the new format is slowly gaining adoption across the industry.

Shift-spacebar to run commands. This is terrific to me – skip the manual, skip memorizing shortcuts for everything, but quickly access commands. (I think a lot of us use Spotlight and other launchers in a similar way, so this is totally logical.)

Transport bar skips by bars and beats. (Wait… why doesn’t every program out there do this, actually?)

Streamlined tools for grid snapping, Region menu, tool swapping, zooming, and more.

Quantize now applies to controllers (CC data), not just notes. (Yes. Good.)

Scalable resolution.

Okay, actually, that last one – I was all set to try the previous version of DP, but discovered it was impossible for my weak eyes to see the UI on my PC. So now I’m in. If you hadn’t given DP a second look because you actually couldn’t see it – it seems that problem is finally solved.

And by the way, you also really see DP’s heritage as a MIDI editor, with event list editing, clear displays of MIDI notes, and more MIDI-specific improvements.

All in all, it looks great. DP has to compete now with a lot of younger DAWs, the popularity of software like Ableton Live, and then the recent development on Windows of Cakewalk (aka SONAR) being available for free. But this looks like a pretty solid argument against all of that – and worth a test.

And I’ll be totally honest here – while I’ve been cursing some of DP’s competition for being awkward to set up and navigate for these same tasks, I’m personally interested.

It means a lot to have one DAW with everything from a mature notation view editor to video scoring to MIDI editing and audio and mixing. It means something you don’t outgrow. But that makes it even more important to have it grow and evolve with you. We’ll see how DP10 is maturing.

64-bit macOS, and 32-bit/64-bit Windows 7/8/10, shipping this quarter.

Pricing:
Full version: $499USD (street price)
Competitive upgrade: $395USD
AudioDesk upgrade: $395USD
Upgrade from previous version: $195USD

http://motu.com/products/software/dp/

I have just one piece of constructive criticism, MOTU. You should change your name back to Mark of the Unicorn and win over millennials. And me, too; I like unicorns.

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ACID Music Studio 11 comes with 64-bit support, new instruments & more

Magix Acid Music Studio 11

Magix has announced the release of ACID Music Studio 11, a completely overhauled version with a powerful 64-bit engine, slick new interface and a wealth of added features and plugins – eight new instruments, six effects and more than 2,500 new ACIDized loops. Besides its new 64-bit architecture, ACID Music Studio 11 comes with the […]

The post ACID Music Studio 11 comes with 64-bit support, new instruments & more appeared first on rekkerd.org.

Synth One is a free, no-strings-attached, iPad and iPhone synthesizer

Call it the people’s iOS synth: Synth One is free – without ads or registration or anything like that – and loved. And now it’s reached 1.0, with iPad and iPhone support and some expert-designed sounds.

First off – if you’ve been wondering what happened to Ashley Elsdon, aka Palm Sounds and editor of our Apps section, he’s been on a sabbatical since September. We’ll be thinking soon about how best to feature his work on this site and how to integrate app coverage in the current landscape. But you can read his take on why AudioKit matters, and if Ashley says something is awesome, that counts.

But with lots of software synths out there, why does Synth One matter in 2019? Easy:

It’s really free. Okay, sure, it’s easy for Apple to “give away” software when they make more on their dongles and adapters than most app developers charge. But here’s an independent app that’s totally free, without needing you to join a mailing list or look at ads or log into some cloud service.

It’s a full-featured, balanced synth. Under the hood, Synth One is a polysynth with hybrid virtual analog / FM, with five oscillators, step sequencer, poly arpeggiator, loads of filtering and modulation, a rich reverb, multi-tap delay, and loads of etras.

There’s standards support up the wazoo. Are you visually impaired? There’s Voice Over accessibility. Want Ableton Link support? MIDI learn on everything? Compatibility with Audiobus 3 and Inter App Audio so you can run this in your favorite iOS DAW? You’re set.

It’s got some hot presets. Sound designer Francis Preve has been on fire lately, making presets for everyone from KORG to the popular Serum plug-in. And version 1.0 launches with Fran’s sound designs – just what you need to get going right away. (Fran’s sound designs are also usually great for learning how a synth works.)

It’s the flagship of an essential framework. Okay the above matters to users – this matters to developers (who make stuff users care about, naturally). Synth One is the synthesizer from the people who make AudioKit. That’s good for making sure the framework is solid, plus

You can check out the source code. Everything is up at github.com/AudioKit/AudioKitSynthOne – meaning Synth One is also an (incredibly sophisticated) example app for Audio Kit.

More is coming… MPE (MIDI Polyphonic Expression) and AUv3 are coming soon, say the developers.

And now the big addition —

It runs on iPhone, too. I have to say, I’ve been waiting for a synth that’s pocket sized for extreme portability, but few really are compelling. Now you can run this on any iPhone 6 or better – and if you’ve got a higher-end iPhone (iPhone X/XS/XR / iPhone XS Max / 6/7/8 Plus size), you’ll get a specially optimized UI with even more space.

Check out this nice UI:

On iPhone:

More:

AudioKit Synth One 1.0 arrives, is universal, is awesome

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