August 2026

No Going Back
AI is accelerating our tools and development processes.
Editorial By J. Martins

  This should be the Acoustics Focus issue of audioXpress. Back in April this year, it became very clear to us that we would need to continue to follow up on what was happening in other fronts, catch up, and move on. Not that we didn't have enough interesting news in acoustics, but there are articles we wanted to get published that had been waiting for too long—not a nice problem to have.

Part of that pressure has to do with the 2026 Audio Engineering Society (AES) Automotive Audio Conference that takes place in Detroit, MI, July 29-31. audioXpress started working on the content related to this important biennial conference earlier on and dedicated its June issue as scheduled to the topic. As this issue is the last one to get distributed before the event, we are pleased to include an important Market Update written by Roger Shively, who is also the Chair of the conference.

The 6th AES International Conference on Automotive Audio will take place at the Huntington Place convention center—in the heart of the American automotive industry. And the topics couldn't be more pressing given the recognized dynamics in the automotive industry and how the role of Automotive Audio has evolved over the past five years. Much more than music playback and communications, sound systems are now used for active sound design, enabled by hardware and software evolving much faster. As the industry is shifting to autonomy and an increasing role of AI-based models and agents, this 2026 conference will provide an overview of the present state-of-the-art in this exciting field and address many of the new scientific disciplines involved.

As I wrote in previous issues, automotive audio is by far the most innovative and fastpaced segment of the audio industry, where every single discipline is converging: AI-based audio enhancement, speech processing, immersive audio, connectivity, and user-adaptive features. North American and European automakers have not yet fully recovered from the shock of seeing the new generations of electric vehicles already dominating the roads in China since 2021, and China is now pushing ahead faster and further with AI on all those fronts.

The cars that are being introduced in China are different in every other way. They offer a completely different experience to the driver and the passengers, starting with sophisticated, premium audio systems and functional voice assistant interfaces (in Chinese) and ending up in never-before-seen features that are evolving in parallel with smartphones, online services, and consumer technology in general.

Evolution and iteration are happening much faster in China. The only areas where the playing field remains leveled for the whole automotive industry have to do with the processors where these systems run—mostly with provenance outside of China, but not for much longer—and of course the software.

Software-defined architectures can quickly transform any vehicle cabin and enable introducing completely new features faster than ever. As vehicles evolve toward fully integrated software frameworks, the vision can also evolve faster. And China seems to have set a mission that is far more ambitious than anyone else with physical AI, AI agent orchestration, and of course robotics. As it was visible recently in the Beijing auto show, where the Western press reported with surprise to the fact that China's automakers were showing humanoid robots and flying cars, the goal is to use the same AI at the core to deliver on the same, bigger vision.

Among the things that I would say require urgent attention from professionals in the audio industry is narrowing the gap between simulation and measurements. I have been in the field with Treble Technologies, the company from Iceland that is pioneering things such as accurate acoustic simulation, and evaluating automatic speech recognition (ASR) models under realistic far-field acoustic conditions, allowing manufacturers to predict speech recognition in real-world deployments, and that gap is becoming more relevant than ever. And nowhere else have I seen better examples of how to effectively connect our increasingly sophisticated multi-physics simulations with measurements in the physical world than in the R&D efforts conducted by automotive companies.

With AI accelerating our tools and development processes, the need to improve prediction accuracy, and consequently our ability to characterize the real world has never been greater.

J. Martins
Editor-in-Chief

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