Adaptive Hearing Aid Beamforming for Multiple Target Positions
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Solution Overview
Problem
Existing hearing devices struggle with directional noise reduction when sound sources originate from multiple positions, as conventional beamformers assume a single target direction, leading to suboptimal signal-to-noise ratios.
Innovation Solution
The use of a Generalized Eigen Vector (GEV) beamformer that adaptively optimizes weights to maximize the signal-to-noise ratio (SNR) for multiple target positions by determining beamformer weights based on inter-microphone covariance matrices and steering vectors, allowing for multiple sound sources to be considered as targets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional beamformers assume a single target direction, then the device complexity remains low, but the signal-to-noise ratio deteriorates when multiple sound sources are present
Solution Approach 1:
The patent segments the single target assumption into multiple discrete target positions. Instead of treating noise reduction as a single-direction problem, the system divides the acoustic space into multiple potential target positions and processes each position separately through multiple beamformers, each optimized for a specific position. This segmentation allows the system to handle multiple sound sources effectively while maintaining manageable complexity for each individual beamformer.
Solution Approach 2:
The patent creates a universal noise reduction system that can handle multiple target positions simultaneously. By designing beamformers that are position-specific yet part of a unified multi-position framework, the system achieves multi-functionality where a single noise reduction apparatus can adapt to various acoustic scenarios (single target, multiple targets, different positions) without requiring completely different processing approaches for each case.
2Adaptability or versatility
If beamformer weights are optimized for a single target position, then the computational load is reduced, but the adaptability to handle multiple sound sources deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-computing and storing beamformer weights for multiple target positions before actual noise reduction is needed. During operation, the system simply selects and applies the pre-computed weights corresponding to the detected target positions, rather than performing complex real-time optimization for each position. This preliminary computation significantly reduces the computational load during actual use while maintaining high adaptability to multiple sound sources.
Solution Approach 2:
The patent introduces dynamics by making the beamformer configuration adaptable to changing acoustic environments. The system dynamically selects which target positions to process and adjusts the number of active beamformers based on the actual number and positions of sound sources present. This dynamic adaptation allows the system to scale its computational complexity according to the situation, maintaining high versatility while avoiding unnecessary computational overhead when fewer targets are present.
Data Source
AI summary
A hearing aid comprises a multitude M≥2 microphones adapted for providing M electric input signals (x) representative of an environment of a user, at least one beamformer for generating at least one beamformed signal in dependence of beamformer weights (w) configured to be applied to said electric input signals, thereby providing said at least one beamformed signal (Y) as a weighted sum of the M of electric input signals. The beamformer weights (w) are adaptively optimized to a plurality of target positions (θ) by maximizing a target signal to noise ratio (SNR) for sound from the target positions (θ).