Adaptive Noise Suppression for Spatial Audio Artifacts
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Solution Overview
Problem
Current spatial audio capture systems face challenges in optimally setting tuning parameters for object separation and noise suppression, leading to suboptimal output quality due to tradeoffs and compromises in manual tuning, which can result in amplified noise and artifacts.
Innovation Solution
An adaptive control mechanism is implemented to adjust noise suppression and object separation parameters based on the spectral characteristics of audio objects and ambient sounds, using techniques like beamforming and machine learning to separate audio signals into object and ambience parts and apply noise suppression, thereby improving perceived audio quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise suppression techniques are applied to spatial audio capture, then noise sources such as wind noise, background noise, motor noise, and handling noise are suppressed, but noise removal artifacts are introduced and audio quality is degraded
Solution Approach 1:
The system dynamically adjusts noise suppression parameters based on the detected audio scene characteristics. By changing parameters adaptively rather than using fixed settings, the system optimizes the balance between noise suppression effectiveness and artifact generation, applying stronger suppression when appropriate and reducing it when it would cause harmful artifacts
Solution Approach 2:
The noise suppression system transitions from static manual tuning to dynamic adaptive control. The system continuously monitors audio characteristics and adjusts suppression levels in real-time, allowing optimal performance across varying acoustic conditions while minimizing artifact generation through context-aware parameter adjustment
2Object-affected harmful factors
If manual tuning is used for noise suppression parameters, then some level of noise suppression is achieved, but output quality is suboptimal due to tradeoffs and compromises
Solution Approach 1:
The system implements feedback mechanisms that monitor audio scene characteristics and use this information to adjust noise suppression parameters. This closed-loop approach replaces manual tuning with automated adaptive control, continuously optimizing the balance between noise suppression and audio quality based on real-time conditions
Solution Approach 2:
The noise suppression system becomes self-adjusting by automatically analyzing audio characteristics and tuning its own parameters. This self-service capability eliminates the need for manual intervention while achieving optimal performance adaptively, with the system serving itself by making real-time parameter adjustments based on detected audio conditions
3Manufacturing precision
If adaptive control mechanism is implemented to adjust noise suppression parameters, then audio quality is enhanced by minimizing artifacts, but device complexity increases
Solution Approach 1:
The adaptive noise suppression system is divided into distinct functional modules: audio scene analysis module, parameter adjustment module, and noise suppression module. This segmentation allows complex adaptive processing to be organized into manageable components, making the system more implementable while maintaining the benefits of adaptive control for reduced artifacts and improved audio quality
Data Source
AI summary
An apparatus configured to: obtain at least two audio signals; obtain, via a network transport channel, an orientation of a user; and determine, with respect to the at least two audio signals, an audio object part and an ambience audio part based, at least partially, on the orientation of the user.