Hearing Aid Beam Former Smoothing Unit for Acoustic Adaptation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Adaptive directionality in hearing aids faces challenges in fluctuating acoustic environments, where fast parameter estimation leads to high variance and poorer performance in steady environments, and existing methods struggle with multiple sound sources active at different times.
Innovation Solution
A hearing aid with an adaptive beam former filtering unit that implements a smoothing scheme for adaptive parameters, using a noise covariance matrix and varying time constants based on environmental changes, to improve noise attenuation while preserving sound from the target direction.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the adaptive system reacts fast in fluctuating acoustic environments, then the hearing aid can quickly adapt to changes in noise and sound sources, but the parameter estimates will have high variance leading to poorer performance
Solution Approach 1:
The patent applies dynamics by making the smoothing parameter μ time-varying rather than fixed. The smoothing parameter is adapted dynamically based on the estimated signal-to-noise ratio and the rate of change of acoustic parameters. When the acoustic environment changes rapidly, the smoothing parameter decreases to allow faster adaptation. When the environment is stable, the smoothing parameter increases to reduce variance and improve performance stability.
Solution Approach 2:
The patent changes the parameter μ (smoothing factor) based on the estimated signal-to-noise ratio and environmental conditions. By adjusting this parameter dynamically, the system optimizes the trade-off between tracking speed and estimation accuracy. The parameter μ is set to smaller values when fast adaptation is needed and larger values when stability is prioritized, resolving the contradiction between adaptation speed and performance reliability.
2Reliability
If smoothing is applied to reduce parameter variance, then performance in steady environments improves, but the system reacts slower to changes in fluctuating environments
Solution Approach 1:
The system dynamically adjusts the smoothing parameter μ based on the estimated rate of change of acoustic parameters and signal-to-noise ratio. When environmental changes are detected, the smoothing parameter is reduced to enable faster reaction. When the environment is stable, the smoothing parameter is increased to reduce variance and improve performance stability, thus resolving the contradiction between reaction speed and performance stability.
Solution Approach 2:
The system uses feedback from the estimated signal-to-noise ratio and the rate of change of acoustic parameters to adjust the smoothing parameter. This feedback mechanism allows the system to automatically optimize the smoothing level based on current environmental conditions, enabling fast reaction when needed and stable performance when the environment is steady.
3Measurement precision
If adaptive beam forming is used to attenuate noise, then speech intelligibility improves, but the system struggles when multiple sound sources are active at different points in time
Solution Approach 1:
The system dynamically adapts the beam pattern based on the estimated direction of arrival and characteristics of active sound sources. When multiple sound sources are detected at different times, the system updates the beam pattern to track and preserve the target speech while attenuating other sources. This dynamic adaptation allows the system to maintain speech intelligibility in complex acoustic environments with multiple talking participants.
Data Source
AI summary
A hearing aid comprises a resulting beam former (Y) for providing a resulting beamformed signal YBF based on first and second electric input signals IN1 and IN2, first and second sets of complex frequency dependent weighting parameters W11(k), W12(k) and W21(k), W22(k), and a resulting complex, frequency dependent adaptation parameter β(k). β(k) may be determined as <C2*·C1>/<(|C2|2>+c), where * denotes the complex conjugation and (·) denotes the statistical expectation operator, and c is a constant, and wherein said adaptive beam former filtering unit (BFU) comprises a smoothing unit for implementing said statistical expectation operator by smoothing the complex expression C2*·C1 and the real expression |C2|2 over time. Alternatively, β(k) may be determined from the following expressionβ=wC1HCvwC2wC2HCvwC2,where wC1 and wC2 are the beamformer weights representing the first (C1) and the second (C2) beamformers, respectively, Cv is a noise covariance matrix, and H denotes Hermitian transposition. Corresponding methods of operating a hearing aid, and a hearing aid utilizing smoothing β(k) based on adaptive covariance smoothing are disclosed.