Efficient acoustic perception for virtual AI agents

Author:

Chemistruck Mike1,Allen Andrew1,Snyder John2,Raghuvanshi Nikunj2

Affiliation:

1. Microsoft Mixed Reality, USA

2. Microsoft Research, USA

Abstract

We model acoustic perception in AI agents efficiently within complex scenes with many sound events. The key idea is to employ perceptual parameters that capture how each sound event propagates through the scene to the agent's location. This naturally conforms virtual perception to human. We propose a simplified auditory masking model that limits localization capability in the presence of distracting sounds. We show that anisotropic reflections as well as the initial sound serve as useful localization cues. Our system is simple, fast, and modular and obtains natural results in our tests, letting agents navigate through passageways and portals by sound alone, and anticipate or track occluded but audible targets. Source code is provided.

Publisher

Association for Computing Machinery (ACM)

Subject

Computer Graphics and Computer-Aided Design,Computer Science Applications

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Toward a human-like sound perception for reactive virtual agents;Proceedings of the 23rd ACM International Conference on Intelligent Virtual Agents;2023-09-19

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