15 August 2023

Full bandwidth wave-based simulations using Treble

Abstract

The study measured the capabilities of Treble’s wave-based solver in a medium-sized room of 80 cubic meters. The solver was tested for full-bandwidth up to 8kHz and both mono and binaural room impulse responses (RIR) were measured using a directive source and a KEMAR mannequin at various positions. The simulations were carried out on a cluster with six Nvidia A100 GPU cards running in parallel. Results are compared and presented for Energy Decay Curves and derived acoustical parameters, reverberation time T20 and early decay time, for the mono RIR. The binaural RIR results are compared both in the frequency domain and in the time domain.

What you'll find

  • Full bandwidth wave-based virtual acoustics with directive sources and receivers.
  • Simulated binaural rendering using 16th order ambisonics using an virtual spherical microphone array.
  • Simulated results showing an excellent match with measurements up to 8kHz.



For more information about our technology, you can read our knowledge base.
For more information about the importance and future of acoustic engineering, read our insight paper.

You can also find more validation studies such as:
-Treble simulation of empty rectangular rooms with porous absorbers

Recent posts

06 January 2026

Meet Treble at CES 2026

At CES we will present the Treble SDK, our cloud based programmatic interface for advanced acoustic simulation. The SDK enables high fidelity synthetic audio data generation, scalable evaluation of audio ML models and virtual prototyping of audio products. Visit us in Las Vegas from January 6-9, 2026 at booth 21641.
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Treble and Hugging Face Collaborate to Advance Audio ML

Treble Technologies and Hugging Face have partnered to make physically accurate acoustic simulation data openly accessible to the global research community. As part of this collaboration, we are releasing the Treble10 dataset, a new open dataset containing broadband room impulse responses (RIRs) and speech-convolved acoustic scenes from ten distinct furnished rooms. The dataset is now freely available on the Hugging Face Hub for non-commercial research. This collaboration aims to lower the barrier to entry for audio and speech machine learning research by providing high-quality, physics-based acoustic data that was previously difficult to obtain or reproduce.