Time-Frequency Matrix for Spatial Audio Playback
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Solution Overview
Problem
Existing technologies struggle to effectively create multi-channel soundfield signals that accurately replicate the original acoustic scene captured by multiple microphones, leading to suboptimal audio playback experiences.
Innovation Solution
The proposed solution involves using a time-and frequency-varying matrix to process multi-microphone input signals, where the matrix is derived based on the dominant direction of arrival and a steering strength parameter, which are determined from characteristics of the input signals such as inter-channel amplitude and group-delay differences.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional audio processing methods are used to create multi-channel soundfield signals, then the processing is simpler, but the playback experience does not accurately approximate the original acoustic scene
Solution Approach 1:
The patent applies dynamics by making the mixing matrix time-varying and frequency-dependent. The matrix adapts to changing acoustic scenes in real-time, allowing the system to track and reproduce the original acoustic environment accurately. This resolves the contradiction by using dynamic adaptation to achieve high fidelity without requiring overly complex static processing structures.
Solution Approach 2:
The patent changes parameters of the mixing matrix based on characteristics of the input signal, specifically using inter-channel amplitude and group-delay differences to determine the matrix configuration. This allows the system to adjust its processing behavior according to the actual acoustic scene, achieving accurate reproduction while maintaining manageable complexity through parameter-based adaptation.
2Reliability
If a time-and frequency-varying matrix is used to accurately replicate the acoustic scene, then the playback quality improves, but the processing complexity increases
Solution Approach 1:
The mixing matrix parameters are changed based on measurable characteristics of the input signal, specifically inter-channel amplitude differences and group-delay differences. This allows the system to achieve high reliability in spatial audio representation by adapting to the actual acoustic scene, while the complexity is managed through systematic parameter adjustment rather than arbitrary complex processing.
Solution Approach 2:
The system performs self-service by automatically determining the mixing matrix configuration from the input signal characteristics themselves. The inter-channel amplitude and group-delay differences in the multi-microphone input are used directly to derive the matrix parameters, allowing the system to adapt to the acoustic scene without requiring external calibration or overly complex processing algorithms.
3Measurement precision
If the mixing matrix is derived from signal characteristics like inter-channel amplitude and group-delay differences, then the acoustic scene approximation improves, but the processing time increases
Solution Approach 1:
The patent extracts and utilizes signal characteristics (inter-channel amplitude and group-delay differences) that are inherently present in the multi-microphone input signal. By using these pre-existing characteristics directly to determine the mixing matrix, the system achieves accurate direction of arrival estimation without requiring additional time-consuming measurement or calibration steps.
Data Source
AI summary
Disclosed are methods and systems which convert a multi-microphone input signal to a multichannel output signal making use of a time-and frequency-varying matrix. For each time and frequency tile, the matrix is derived as a function of a dominant direction of arrival and a steering strength parameter. Likewise, the dominant direction and steering strength parameter are derived from characteristics of the multi-microphone signals, where those characteristics include values representative of the inter-channel amplitude and group-delay differences.