Spatial Audio Rendering via Semantic Signal Decomposition
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Solution Overview
Problem
Conventional audio processing methods face challenges in achieving high perceptual quality for noise-like signals and ambience materials, such as applause and natural environments, due to unsatisfactory quality or high computational complexity, particularly in decorrelating and up-mixing processes.
Innovation Solution
The approach involves decomposing audio signals into foreground and background components, which are then processed separately based on their semantic properties, allowing for adaptive spatial rendering and decorrelation, thereby improving perceptual quality while maintaining moderate computational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional decorrelation methods are used for noise-like signals and ambience materials, then spatial audio rendering can be achieved, but perceptual quality becomes unsatisfactory
Solution Approach 1:
The input audio signal is decomposed into multiple semantic signal components (e.g., foreground events like handclaps and background ambience). Each component is processed independently through separate rendering paths, allowing tailored spatial processing for different signal types while maintaining overall system efficiency.
Solution Approach 2:
Different rendering characteristics are applied to different signal components based on their semantic properties. Foreground components receive one type of spatial processing while background components receive another, optimizing perceptual quality for each component's specific characteristics rather than applying a uniform approach.
2Reliability
If object-orientated approaches are used to model auditory events, then spatial audio quality improves, but computational complexity increases due to the number of auditory events to be processed
Solution Approach 1:
The audio signal is segmented into semantic components that group similar auditory events together. Instead of processing each individual auditory event separately, the system processes groups of events with similar characteristics through shared rendering paths, significantly reducing computational complexity while maintaining spatial audio quality.
Solution Approach 2:
The system changes the parameter representation from individual event-based modeling to semantic component-based modeling. By transforming the problem from processing numerous discrete auditory events to processing a smaller number of semantic signal components with distinct characteristics, computational complexity is reduced while preserving spatial rendering quality.
3Reliability
If strong decorrelation is applied to restore ambience sensation, then spatial immersion improves, but transient event quality degrades due to temporal smearing effects
Solution Approach 1:
The system separates transient events (foreground) from ambience signals (background) into different signal components. This segmentation allows applying different rendering characteristics to each component: mild processing for transients to preserve their sharpness and strong decorrelation for background ambience to enhance spatial immersion, thereby resolving the contradiction between the two quality requirements.
Solution Approach 2:
Different levels of decorrelation strength are applied locally to different signal components based on their semantic properties. Foreground transient components receive processing that preserves temporal precision, while background ambience components receive stronger decorrelation to enhance spatial immersion. This local differentiation resolves the contradiction by optimizing each component for its specific quality requirements.
Data Source
Figure 1A
Figure 1B
Figure 2~3
AI summary
An apparatus (100) for determining a spatial output multi-channel audio signal based on an input audio signal and an input parameter. The apparatus (100) comprises a decomposer (110) for decomposing the input audio signal based on the input parameter to obtain a first decomposed signal and a second decomposed signal different from each other. Furthermore, the apparatus (100) comprises a renderer (110) for rendering the first decomposed signal to obtain a first rendered signal having a first semantic property and for rendering the second decomposed signal to obtain a second rendered signal having a second semantic property being different from the first semantic property. The apparatus (100) comprises a processor (130) for processing the first rendered signal and the second rendered signal to obtain the spatial output multi-channel audio signal.