arXiv:2509.15210v2 Announce Type: replace-cross Abstract: Realistic sound simulation plays a critical role in many applications. A key element in sound simulation is the room impulse response (RIR), which characterizes how sound propagates within a given space. Recent studies have applied neural implicit methods to learn RIR using context information collected from the environment, such as scene images. However, these approaches do not effectively leverage explicit geometric information from the environment. To further exploit neural implicit models with direct geometric features, we present M
The paper builds on recent advancements in neural implicit methods, suggesting a continuous evolution in AI-driven sound simulation technology and its applications.
This development can significantly enhance the realism and efficiency of sound simulation across various applications, from virtual reality to architectural acoustics.
The ability to more explicitly integrate geometric information into neural RIR generation improves fidelity, potentially leading to more accurate and immersive synthetic audio environments.
- · Virtual Reality/Augmented Reality developers
- · Gaming industry
- · Acoustic engineering firms
- · AI-driven simulation platforms
- · Traditional RIR measurement companies (potentially, in some niches)
Improved realism in simulated audio environments will enhance user experience and application effectiveness.
The reduced need for extensive real-world acoustic measurements could accelerate development cycles in sound-sensitive applications.
More accessible and high-fidelity sound simulation tools could democratize advanced audio design across various industries.
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Read at arXiv cs.AI