Spatial Sound Characterization Using Time-Frequency Segmentation
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Solution Overview
Problem
Existing methods for spatial sound characterization struggle with accurately localizing multiple sound sources in real-time, especially in reverberant environments, and often result in computational inefficiencies and musical noise during source separation.
Innovation Solution
A processor-implemented method that segments source signals into time frames, applies time-frequency transforms, estimates the number and directions of sources, and uses beamforming and post-filtering to separate and reproduce spatial sound, incorporating W-disjoint orthogonality conditions and binary masks to enhance source separation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing methods are used for spatial sound characterization, then source localization can be performed, but computational complexity is high and accuracy deteriorates in reverberant environments
Solution Approach 1:
The patent segments the sound signal into multiple time frames and processes each frame independently to estimate direction of arrival. This temporal segmentation reduces the computational burden compared to processing the entire signal at once, while improving localization accuracy by adapting to time-varying acoustic conditions in reverberant environments.
Solution Approach 2:
The patent transforms the spatial sound characterization problem from the time domain to the frequency domain using time-frequency transforms. This dimensional transformation enables more accurate source separation and localization by exploiting frequency-dependent spatial characteristics, particularly effective in reverberant environments where different frequencies experience different levels of reverberation.
2Productivity
If source separation is performed without W-disjoint orthogonality conditions, then source signals can be extracted, but musical noise is generated during separation
Solution Approach 1:
The patent applies W-disjoint orthogonality conditions that modify the separation parameters by enforcing zero correlation between separated sources at different time-frequency points. This parameter constraint eliminates musical noise artifacts while maintaining efficient source separation, as the orthogonality condition ensures that energy from different sources does not leak into each other's spectral components.
3Device complexity
If simple spatial separation is used, then computational load is reduced, but spatial impression and sound quality are degraded
Solution Approach 1:
The patent introduces beamforming as an intermediary spatial filtering technique between the microphone array and source separation. The beamformer acts as a mediator that enhances signals from specific directions while suppressing others, preserving spatial impression. This intermediary processing layer maintains sound quality by selectively amplifying direct sound paths before the more computationally intensive separation stage.
Solution Approach 2:
The patent performs preliminary spatial filtering using beamforming before conducting full source separation. This preliminary action pre-processes the spatial characteristics of the signal, organizing energy by direction of arrival. By establishing this preliminary spatial structure, the subsequent separation process requires less computational effort to maintain high spatial impression quality, as the beamforming has already organized the spatial information.
Data Source
AI summary
A processor-implemented method for spatial sound characterization is described. In one implementation, each of a plurality of source signals detected by a plurality of sensing devices, is segmented into a plurality of time frames. For each time frame, time-frequency transform of the source signals is derived, an estimated number of sources and at least one estimated direction of arrival corresponding to each of the source signals is obtained. Further, source signals are extracted by spatial separation based at least on the estimated directions of arrival and the estimated number of sources, and separated source signals are processed to yield a reference signal and side information.