Multi-Device Audio Capture Relevance Selection
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Solution Overview
Problem
Existing methods for capturing multi-view audio struggle with accurately combining audio signals from multiple recording devices, especially in scenarios with inaccurate or unavailable device position measurements, leading to compromised audio quality and increased complexity, particularly in large-scale events.
Innovation Solution
A method that selects recording devices based on relevance levels determined by their perceptual importance, combining only the audio signals from relevant devices to generate high-quality combined audio signals, regardless of device positions, using techniques like similarity analysis and relevance ranking.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If audio signals from all recording devices are combined, then audio coverage is improved, but computational complexity increases significantly
Solution Approach 1:
The patent extracts and combines only the most relevant audio signals from recording devices based on their proximity to the listening position, rather than combining all available signals. This selective extraction approach maintains audio coverage quality while significantly reducing computational complexity by processing only a subset of signals.
Solution Approach 2:
The patent applies local quality by prioritizing recording devices based on their spatial relationship to the desired listening position. Devices closer to the listening position are given higher relevance and their signals are combined with greater weight, creating a locally optimized audio mixture that improves efficiency without sacrificing coverage.
2Measurement precision
If device position measurements are used to select recording devices, then selection accuracy is improved, but measurement precision requirements increase system complexity
Solution Approach 1:
The patent implements self-service by allowing recording devices to autonomously determine their own relevance based on simple position measurements and the listening position information. Each device calculates its own relevance metric without requiring complex centralized processing or high-precision measurement infrastructure, reducing overall system complexity.
Solution Approach 2:
The patent changes the parameter of position measurement precision requirements by using relative position information and relevance calculations that work with moderate-precision measurements. Instead of requiring high-precision absolute positioning, the system uses parameter transformations that convert position data into relevance scores, allowing accurate device selection with simpler measurement systems.
3Measurement precision
If relevance levels are calculated for all recording devices, then selection accuracy is improved, but processing time increases
Solution Approach 1:
The patent segments the set of recording devices into relevance groups based on simplified criteria such as distance thresholds or signal strength ranges. Instead of calculating detailed relevance levels for all devices, the system divides them into segments (e.g., near-field, mid-field, far-field devices) and processes each segment with appropriate selection criteria, reducing overall processing time while maintaining selection accuracy.
Data Source
AI summary
It is inter alia disclosed to select, by a first apparatus, one or more recording devices to obtain a set of selected recording devices, or to receive, at the first apparatus, information on a set of one or more selected recording devices. The selected recording devices in the set of selected recording devices are selected from a set of recording devices at least based on relevance levels determined for the recording devices of the set of recording devices. A combination of audio signals recorded by the selected recording devices of the set of selected recording devices in an audio scene to obtain one or more combined audio signals for rendering is performed or caused by the first apparatus.