Hearing Aid Target Quality Assessment for Adaptive Beamforming
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Solution Overview
Problem
Conventional voice activity detection (VAD)-driven speech signal processing in hearing aids often leads to output signals with residual noise, distorted speech, or reduced intelligibility due to mis-steered beamformers and over/under-suppressed noise reduction, resulting in less than optimal speech quality and intelligibility.
Innovation Solution
A hearing aid system with multiple beamformers steered towards different directions, each with unique processing parameters, combined with a target quality assessment unit to determine assessment values, and a modification unit to adjust processing parameters based on these values, ensuring improved speech enhancement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise reduction algorithms are applied to suppress residual noise, then noise level is reduced, but speech intelligibility and quality deteriorate due to over-suppression
Solution Approach 1:
The system employs a feedback mechanism where the target quality assessment unit continuously evaluates the processed signal and provides feedback to the modification unit. This feedback loop allows the system to adjust processing parameters dynamically, preventing over-suppression while maintaining noise reduction effectiveness. The assessment values guide the modification unit to fine-tune the second processing parameter, ensuring speech quality is preserved.
Solution Approach 2:
The invention changes processing parameters based on assessment values. The modification unit adjusts the second processing parameter (e.g., noise reduction strength, beamforming weights) according to the assessment values from the target quality assessment unit. This parameter adaptation allows the system to optimize the balance between noise suppression and speech preservation, avoiding both under-suppression and over-suppression.
2Reliability
If beamforming algorithms are applied to enhance target signal, then speech quality is improved, but mis-steering occurs leading to degraded target signal and reduced noise suppression
Solution Approach 1:
The target quality assessment unit provides continuous feedback on beamforming performance, allowing the modification unit to adjust beamformer steering parameters. This feedback mechanism ensures the beamformer remains accurately steered toward the target speech source while maintaining optimal noise suppression, preventing mis-steering issues.
Solution Approach 2:
The system dynamically adjusts beamforming parameters based on real-time assessment values. The modification unit continuously optimizes the second processing parameter according to the assessment of target signal quality, enabling the beamformer to adapt to changing acoustic environments and maintain accurate steering without manual intervention.
3Object-affected harmful factors
If fast gain fluctuations are introduced to enhance noise reduction, then noise suppression is improved, but output signal contains unnatural modulations reducing quality
Solution Approach 1:
The modification unit adjusts processing parameters based on assessment values to control gain fluctuations. By fine-tuning the second processing parameter according to target quality assessment, the system achieves effective noise suppression while maintaining natural signal characteristics, avoiding unnatural modulations in the output.
Data Source
AI summary
Disclosed herein are embodiments of a hearing aid. The hearing aid can include an input unit configured to provide an electrical audio input signal representing a sound, a signal processing unit configured to provide a processed signal based on the electrical audio input signal using a first processing parameter, and a target quality assessment unit configured to determine an assessment value based on the processed signal. The signal processing can be is configured to determine an output signal based on the assessment value.