Voxel-Based Audio Filter Selection for Acoustic Simulation
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Solution Overview
Problem
Conventional methods for simulating realistic sound in media environments are computationally complex and require human-intensive hard coding, making it difficult to adapt to changes in the media environment.
Innovation Solution
The use of a voxel-based representation of 3D media environments allows for real-time acoustic adjustments by calculating sound propagation and reverberation, using a shape matrix to select appropriate audio filters based on environmental characteristics, reducing computational complexity and enabling adaptive audio processing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional methods are used to simulate realistic sound, then acoustic realism is improved, but computational complexity and processing requirements increase significantly
Solution Approach 1:
The environment is divided into voxels (volume pixels) that are segmented and processed individually. Each voxel represents a small volumetric element of the 3D space, allowing the system to analyze acoustic properties by processing discrete segments rather than the entire environment as a single complex calculation unit. This segmentation enables efficient determination of listener and emitter positions within the voxel grid.
Solution Approach 2:
The patent creates a simplified computational model (voxel-based representation) that copies the essential geometric and acoustic characteristics of the real 3D environment. Instead of performing complex acoustic simulations on the actual environment geometry, the system uses a copied voxel representation that preserves spatial relationships and boundary information needed for acoustic calculations, significantly reducing processing requirements while maintaining realism.
2Manufacturing precision
If hard coding is used for specific sound environments, then audio accuracy for predefined environments is improved, but adaptability to changes and new environments deteriorates
Solution Approach 1:
The system dynamically determines acoustic properties based on the current voxel-based environment representation rather than using static hard-coded values. As the listener or sound emitter moves through the voxel grid, or as the environment changes, the system recalculates acoustic characteristics in real-time by analyzing the updated voxel configuration. This dynamic approach allows the same code to adapt to any environment configuration without requiring pre-programming for each specific scenario.
Solution Approach 2:
The system automatically analyzes the voxel-based environment representation to determine acoustic properties without requiring manual configuration or hard-coding for each environment. The algorithm self-adapts by processing the voxel data structure to identify boundaries, calculate distances, and determine acoustic characteristics autonomously, eliminating the need for human-intensive hard coding while maintaining audio accuracy.
3Reliability
If detailed acoustic simulation is performed, then sound realism is improved, but processing power and memory requirements increase
Solution Approach 1:
The continuous 3D space is segmented into discrete voxels of uniform size, transforming the acoustic simulation problem from a continuous complex calculation into a discrete grid-based analysis. This segmentation allows the system to process only relevant voxels near the listener and sound emitter rather than analyzing the entire environment, significantly reducing the number of calculations required while preserving acoustic realism through proper voxel boundary detection.
Solution Approach 2:
The system performs acoustic calculations only for the necessary portion of the environment - specifically analyzing voxels in the immediate vicinity of the listener and sound emitter rather than the entire 3D space. By applying acoustic processing selectively to relevant regions (partial action) rather than the complete environment, the system achieves realistic sound simulation with reduced computational effort and lower processing power requirements.
Data Source
AI summary
One example method for processing sound in a computer environment includes recognizing a location of a listener in the computer environment, identifying a shape matrix including, for each of a plurality of vectors intersecting the location of the listener, a distance from the location of the listener to an environmental boundary of the computer environment along the vector, selecting an audio filter based on the shape matrix, and outputting sound filtered by the audio filter.