Steerable Audio Beam Prediction for AR Clarity
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Solution Overview
Problem
Current AR and VR systems lack customization in audio processing, failing to account for device movement or multiple device locations, leading to suboptimal audio reception and clarity, especially in environments with poor acoustics or multiple users.
Innovation Solution
The system accesses environment data to identify sound sources and steers audio beams dynamically, anticipating the movement of sound sources by using historical data and sensor information to ensure clear audio reception, employing beamforming techniques and active noise cancellation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If standard audio processing is used in AR/VR devices, then device complexity is reduced, but audio clarity and intelligibility deteriorate in complex environments
Solution Approach 1:
The system performs preliminary actions by predicting future sound source locations using historical movement data before the sound sources actually move there. This allows the audio beam to be pre-positioned, maintaining audio clarity without requiring complex real-time tracking adjustments. The beam is steered to anticipated locations in advance, resolving the contradiction between audio quality and processing complexity.
Solution Approach 2:
The audio beam steering is made dynamic by continuously updating beam direction based on predicted sound source movements rather than static positioning. The system adapts beam orientation in real-time according to environmental data and historical patterns, achieving high audio clarity in moving environments without proportionally increasing processing complexity through rigid real-time tracking.
2Manufacturing precision
If audio beams are steered to track sound sources in real-time, then audio reception quality improves, but loss of time occurs due to continuous adjustment delays
Solution Approach 1:
The system eliminates time loss by performing preliminary beam steering to predicted sound source locations before the sound sources actually arrive at those positions. Using historical movement data, the system anticipates future positions and pre-positions audio beams, thereby maintaining audio reception quality without experiencing delays associated with reactive real-time tracking adjustments.
3Adaptability or versatility
If environmental data from multiple AR/VR devices is processed, then adaptability to complex environments improves, but device complexity and data processing requirements increase
Solution Approach 1:
The system achieves environmental adaptability through a universal prediction model that processes environmental data from multiple AR/VR devices using the same historical movement patterns and beamforming algorithms. This multi-functional approach handles diverse environmental scenarios (different numbers of sound sources, various movement patterns) with a unified processing framework, maintaining adaptability while controlling processing complexity through algorithmic efficiency.
4Measurement precision
If historical movement data is used to predict sound source locations, then audio beam accuracy improves, but loss of information occurs when sound sources move unpredictably
Solution Approach 1:
The system maintains location accuracy through dynamic adaptation of prediction models. When sound sources exhibit unpredictable movement, the system continuously updates its historical movement data and adjusts beam steering accordingly. This dynamic approach preserves measurement precision by adapting to changing movement patterns while minimizing information loss about unpredictable behaviors through continuous data refreshment.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach enhances audio clarity and intelligibility for users by focusing audio beams on intended sound sources, even in complex environments, improving the overall AR and VR experience.
Implementation Method 1
The device may include audio hardware components that are configured to generate such steerable audio beams. The method may also include identifying the location of the sound source within the environment based on the accessed environment data, and then steering the audio beams of the device to the identified location of the sound source within the environment.
Data Source
AI summary
The disclosed computer-implemented method for performing directional beamforming according to an anticipated position may include accessing environment data indicating a sound source within an environment. The device may include various audio hardware components configured to generate steerable audio beams. The method may also include identifying the location of the sound source within the environment based on the accessed environment data, and then steering the audio beams of the device to the identified location of the sound source within the environment. Various other methods, systems, and computer-readable media are also disclosed.