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‘Embrace the AI revolution’: The growing role of AI in audio workflows

"It’s no secret that AI is quickly becoming a vital cog in the machine"

Francois Quereuil, director of product management, audio workstations and control surfaces at Avid, looks at how AI and audio are becoming ever-more closely intertwined…

Artificial Intelligence (AI) is having a transformative effect on a huge range of industries, and the world of media and entertainment is no exception. Creators and machines are continuing to become more intertwined, with creative workflows taking on new shapes as AI-assistance gathers momentum.

At a broad level, people are recognising that technology and creativity go hand in hand. Creative professionals are expressing an interest in how AI and machine learning can aid the creative process. And although the discussion about machines replacing humans remains prevalent, the reality is much less dystopian. Rather than being worried about losing their jobs to technology, they are recognising the potential for AI-powered tools to make processes more intuitive and reduce the time spent on tedious, uncreative tasks.

When talking about audio specifically, it’s no secret that AI is quickly becoming a vital cog in the machine – and the truth is we’re only just scratching the surface. So, what role is AI currently playing within audio workflows and how is this growing trend likely to develop in the future?

Transforming workflows

When it comes to audio workflows, there are three main areas where AI is starting to have an impact: assisted mastering, assisted mixing and assisted composition. All three are at slightly different points on the adoption scale.

For example, AI is already well established in the mastering process – despite this arguably being the most specialised area of music production. The goal of mastering is to make the listening experience consistent across all formats. The process varies across different formats (Spotify, CDs, movies, etc.) as each has different loudness constraints, making mastering extremely technical and potentially costly.

There are very few skilled mastering engineers around, but AI is proving to be a viable and democratising alternative for many musicians. By analysing data and learning from previous tracks, AI-powered tools enable less experienced engineers to quickly and easily achieve professional results, albeit without the finesse of a human expert.

Next, we come to assisted mixing which, although currently slightly behind mastering in terms of adoption, is developing fast. With so much content being created for OTT services such as Netflix and Amazon Prime, the volume of audio work happening in post is increasing dramatically. Facilities are therefore looking for ways to work faster and more cost-efficiently.

AI tools can help engineers and audio teams make basic decisions and complete the more routine tasks, thereby saving valuable pre-mixing time and enabling humans to focus on the more complex and creative elements.

For example, some mastering plugins contain built-in intelligence that analyses source material (such as guitars or vocals) and puts it in the context of the rest of the mix to suggest mixing decisions. By taking on much of the initial heavy lifting, tools such as this can be hugely beneficial for less experienced users.

Finally, there’s audio composition, another area of music production that is quickly realising the value of AI. More and more tools are using deep learning algorithms to identify patterns in huge amounts of source material and then utilising the insights generated to compose basic tunes and melodies.

They’re by no means perfect. But intuitive, user-friendly AI systems are having a transformative effect on audio workflows.

Preparing for an AI future

The prevalence of AI in audio workflows is only going to gather momentum in the months and years to come. AI could be well suited to up-and-coming artists who don’t rely on music as their primary income and have limited time and resources to dedicate to song writing.

But the real opportunity is in post-production, due to the time- to-market pressures involved. Sound engineers can use AI to speed up and simplify baseline tasks, enabling them to focus on the high- value aspects that require more creativity.

In the long term, AI could be used to manage complex installations and systems. With audio-over-IP, teams manage routing from central software so they can pool resources to support projects. AI could be used to manage these complex networks of computers and software.

Ultimately, we’re at the tip of the iceberg. For beginner and intermediate-level creative professionals, AI tools can act as an assistant that can learn their mixing habits over time and help audio sound the best it possibly can. For more experienced professionals, it can help increase efficiency by removing many of the tedious, time-consuming tasks.

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AI will never replace humans entirely, but it’s clear that the technology is set to play a key role in the years to come as it continues to get more advanced. Audio professionals have to be prepared to embrace the AI revolution.

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