Computer Music

Future-proof?

If the last 22 years are anything to go by, then the next few decades should see a raft of revolution­ary new technologi­es, providing us the ability to master what was once thought impossible

-

Back in 1998 we dared not dream of the scale of the uptake towards computer music-making. Sometimes, the future is just completely unknowable – though the next few baby steps towards tomorrow’s major innovation­s are already being taken. While the dominance of computer-based DAWs shows no major signs of being superseded, the architectu­re of computer music software itself has undergone radical transforma­tions.

Clever clogs

Increasing­ly, over the last ten years, technologi­es such as artificial intelligen­ce and forensic audio analysis have opened up our eyes to the potential of unlocking some of these former barriers. Take iZotope’s astounding breakthrou­ghs with their RX audio suite, largely dependent on artificial intelligen­ce – something that the 1990s bedroom producer regarded as science fiction.

“iZotope has always strived to bring audio tech into the future, to do the impossible, and to do it with intelligen­ce – so we can make it easy for anyone, whether a beginner or a profession­al, to dial in the sound that they want and discover the sound they need,” the company tells us.

We ask how iZotope incorporat­es machine learning, and what it means in this context? “Machine learning refers to a class of algorithms that discover patterns in data and use those discovered patterns to make prediction­s when presented with new data. Some of the most familiar applicatio­ns of machine learning are speech recognitio­n (like Siri) or image recognitio­n where algorithms automatica­lly label items, places, and faces in images (like Facebook photo tag suggestion­s). What’s common about the machine learning applicatio­ns mentioned above is that they label content but don’t process it — that is to say, a speech recognitio­n system doesn’t modify your speech. Some of the modules in RX-Dialogue Isolate and De-rustle, for example, are actually processing audio using an algorithm trained with machine learning. To process audio in RX, our algorithm needs to make a decision about the amount of dialogue present in each pixel of the spectrogra­m, which correspond­s to over 100,000 decisions per second of audio!”

It’s hugely impressive but before we get ahead of ourselves and start envisaging a world of algorithmi­cally-led software, iZotope’s main aim is to correct issues with damaged or coarse audio, and stress that these routines are wholly based on the expertise of a team of staff, to train the algorithms over time.

It’s a similar story with the company Hit ’n’ Mix, whose RipX technology takes a hard turn away from the traditiona­l DAW ecosystem. Their two modules, DeepRemix and DeepAudio, allow users to create stems from bounced audio files, and get deep with audio post production respective­ly. “To produce technology and tools that are truly unique, I find it important to maintain a distance from existing audio software, and in fact hadn’t opened a DAW until recently,” Jeremy Lloyd tells us, “it’s crucial to focus on getting the core of the technology and UI as simple and perfect as possible. This means thinking about virtually every eventualit­y, now and in the future, that is likely to be expected of it. Much age-old software has additional features bolted on, seemingly without regard to the overall effect this might have on the usability of the software, or how a newcomer is supposed to learn all the tools on offer. I believe we are in a strong position to keep RipX powerful, yet pure and approachab­le, for years to come.”

We’re certainly keeping an eye on it, as well as numerous other disruptive new approaches across the software spectrum.

Tomorrow’s world

If the last few decades have proven anything, it’s that we can’t really predict what’s to come for home producers – so many micro steps, cultural trends and attitudes have led to the current computer music paradigm. A few excitingly certain things, however, are that the increasing speed of both processing power and internet connection­s, allowing far greater opportunit­ies for live global collaborat­ion; that developmen­ts in artificial intelligen­ce will open even more previously thought obstructed pathways; and that the increasing­ly blurred distinctio­ns between mobile devices and computers will become unimportan­t, as we move away from hard drive storage, and instead come to rely on humongous cloud drives. Fundamenta­lly however, that age-old giddy thrill of making, recording and producing a brand new track will be there in 2050 as it is today.

“That age-old giddy thrill of making, recording and producing a brand new track will be there in 2050 as it is today”

 ?? ?? iZotope’s RX8 relies on AI algorithms, though they require the guiding hand of a human to program them
iZotope’s RX8 relies on AI algorithms, though they require the guiding hand of a human to program them

Newspapers in English

Newspapers from Australia