AI Acoustic Modelling and Coverage Prediction

For decades, acoustic prediction relied on ray-tracing or beamforming simulations that approximated sound propagation based on simplified physics. These methods required hours of manual computation and often failed to account for complex reflections, diffraction, or real-world variables like temperature gradients and audience absorption.

Even with powerful software like EASE or CATT, engineers had to iterate through dozens of configurations to find an optimal loudspeaker placement and aiming. The process was time-consuming and still left room for on-site surprises — especially in irregular venues like amphitheatres, multi-purpose halls, or outdoor festival grounds.

SSOUNDS integrates AI/ML directly into its system design workflow. Instead of relying solely on theoretical models, our algorithms are trained on tens of thousands of real-world impulse responses, SPL maps, and intelligibility scores from actual deployments across stadiums, theatres, and houses of worship.

The AI learns to predict how sound interacts with specific geometries and materials — even accounting for crowd density and humidity. When an engineer inputs a venue's 3D model, the system rapidly generates a coverage map that shows predicted SPL variation, frequency response uniformity, and speech intelligibility (STI) across every seat.

This process, which once took a full day of manual simulation, now completes in minutes. The AI also suggests optimal array configurations, aiming angles, and subwoofer placements, reducing human error and accelerating the design phase.

Key metrics like SPL distribution and speech intelligibility are critical for live sound. SSOUNDS' AI models predict not just overall level but also spectral balance — ensuring that low-frequency energy doesn't overwhelm the front rows while high frequencies reach the back of the room with clarity.

Intelligibility prediction uses machine learning to simulate how reverberation and early reflections degrade consonant clarity. The AI can highlight zones where STI falls below 0.5 (poor intelligibility) and recommend adjustments — such as adding delay fills or adjusting array curvature — to bring every seat above the threshold.

This level of granularity was previously only achievable with extensive on-site measurement. Now, it's part of the pre-deployment design, saving time and ensuring consistent results.

SSOUNDS uses AI not just for prediction but also for optimisation. Our proprietary software integrates with the loudspeaker's DSP presets, allowing the AI to fine-tune crossover points, EQ, and delay settings based on the predicted acoustic response.

For line arrays, the AI optimises splay angles and number of enclosures to achieve uniform coverage with minimal overlap. For subwoofer arrays, it predicts cancellation patterns and suggests cardioid or end-fire configurations to reduce rearward energy.

The result is a system that arrives on site with a highly accurate prediction of its real-world performance. Tuning time is drastically reduced, and the final sound is consistent with the design intent.

AI models are only as good as their training data. SSOUNDS continuously feeds measurement data from every deployment back into the machine learning pipeline. This creates a virtuous cycle: each new show improves the accuracy of future predictions.

Field engineers use handheld measurement rigs to capture SPL maps and impulse responses, which are uploaded to the cloud. The AI compares predicted vs. actual performance and adjusts its internal weights accordingly. Over time, the system becomes increasingly reliable across diverse venue types and climates.

This commitment to real-world validation ensures that SSOUNDS' AI acoustic modelling remains at the cutting edge — delivering predictable, repeatable results for every client.

Looking ahead, SSOUNDS is developing AI models that can adapt in real time during a performance. By integrating with networked microphones and sensors, the system could detect changes in audience absorption, temperature, or humidity and adjust DSP parameters on the fly.

This would allow the PA to maintain optimal coverage and intelligibility even as conditions change — for example, when a crowd fills in or when the sun sets and the air cools. While still in R&D, this capability represents the next frontier in intelligent sound reinforcement.

SSOUNDS is proud to lead the industry in applying AI to acoustic design, making premium sound more accessible and reliable than ever.