Fractional-Order Ambisonics Rendering for Precise Sound Spread
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Solution Overview
Problem
Ambisonics technology is limited to discrete polynomial orders, which restricts the ability to accurately represent the spatial resolution and spread of sound objects, particularly in virtual reality applications.
Innovation Solution
An apparatus and method that utilize polynomial interpolation to derive fractional Ambisonics orders, applying weights to encode sound objects, and employ techniques like All-Round Ambisonics Decoding (AllRAD) or All-Round Ambisonics Panning (AllRAP) to play sound objects on speakers with a desired spread, combining Vector-Based Amplitude Panning (VBAP) for low or zero spreads.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If discrete polynomial orders are used in Ambisonics, then the encoding process is simple and computationally efficient, but the spatial resolution and spread representation of sound objects are limited
Solution Approach 1:
The patent applies parameter changes by transitioning from discrete integer polynomial orders to continuous fractional orders in the Ambisonics encoding process. This allows the spatial resolution and sound spread representation to be precisely controlled by adjusting the fractional order parameter, thereby resolving the contradiction between measurement precision and device complexity.
2Measurement precision
If higher Ambisonics orders are used, then spatial resolution improves, but computational complexity and processing requirements increase
Solution Approach 1:
The patent implements partial action by introducing fractional orders between integer Ambisonics orders. This allows the system to use only the necessary computational resources for the required spatial resolution, avoiding the excessive computational power demands of full higher-order Ambisonics while still achieving improved spatial resolution when needed.
Data Source
AI summary
Ambisonics audio such as may be used for computer simulations such as computer games is improved by improving the emulated spread of a sound source. A demanded spread for a sound object of a computer game is received, and using the spread one or more fractional Ambisonics orders are determined. Weights such as max-rE weights are derived for the fractional Ambisonics order using polynomial interpolation. An Ambisonics representation of the sound object is encoded using the weights for the fractional Ambisonics order for providing the sound object to an Ambisonics decoder to decode and play the sound object.