Audio Object Clustering With Metadata-Preserving Cluster Allocation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing audio content presentation devices struggle with preserving rendering metadata during audio object clustering, leading to spatial distortion and increased bandwidth requirements, while strict clustering methods either increase complexity or cause perceptual discontinuities.
Innovation Solution
A hybrid approach to audio object clustering that allows flexibility in assigning objects across rendering metadata categories, preserving metadata where necessary and reducing spatial distortion by optimizing cluster allocations and object-to-cluster gains.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If audio objects are clustered without preserving rendering metadata categories, then spatial distortion occurs and bandwidth requirements increase, but if rendering metadata categories are strictly preserved, then metadata integrity is maintained but the number of required clusters increases
Solution Approach 1:
The patent segments the rendering metadata into categories (e.g., virtualization category, bypass category) and processes each category separately during clustering. This allows the system to maintain metadata integrity by preserving category assignments while reducing the overall number of clusters needed, as objects within the same category can be clustered together without violating metadata requirements.
Solution Approach 2:
The patent applies different clustering strategies to different categories of rendering metadata. Instead of applying a uniform clustering approach to all audio objects, the system tailors the clustering process to the specific requirements of each category, allowing for optimized cluster allocation that maintains metadata integrity while minimizing the total number of clusters required.
2Manufacturing precision
If a high number of clusters are used to maintain metadata integrity, then rendering quality is preserved, but signal encoding and transmission become more complex
Solution Approach 1:
The patent merges audio objects into clusters while preserving rendering metadata categories, allowing multiple objects to share common cluster identifiers. This merging approach reduces the number of unique cluster identifiers that need to be encoded and transmitted, thereby simplifying signal encoding and transmission while maintaining rendering quality through category-preserving clustering.
Solution Approach 2:
The patent changes the parameter space from individual audio object attributes to category-based cluster attributes. By transforming the representation from fine-grained object-level parameters to coarser category-level parameters, the system reduces the complexity of signal encoding while preserving the essential rendering quality information needed for accurate audio reproduction.
3Ease of manufacture
If audio objects are assigned to clusters based solely on spatial position, then clustering is simplified, but spatial distortion occurs
Solution Approach 1:
The patent introduces dynamic constraints to the clustering process based on rendering metadata categories. Instead of using a static spatial-only clustering approach, the system dynamically adjusts cluster assignments to respect category boundaries, ensuring that audio objects are clustered in a way that maintains both spatial accuracy and metadata integrity, thereby preventing spatial distortion.
Data Source
AI summary
A method for clustering audio objects may involve identifying a plurality of audio objects, wherein each audio object of the plurality of audio objects is associated with respective metadata that indicates respective spatial position information and respective rendering metadata. The method may involve assigning audio objects of the plurality of audio objects to categories of rendering metadata of a plurality of categories of rendering metadata, wherein at least one category of rendering metadata comprises a plurality of types of rendering metadata to be preserved. The method may involve determining an allocation of a plurality of audio object clusters to each category of rendering metadata. The method may involve rendering audio objects of the plurality of audio objects to an allocated plurality of audio object clusters based on the metadata that indicates spatial position information and based on the assignments of the audio objects to the categories of rendering metadata.