Adaptive Hearing System Processing for Speech and Noise Balance
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Solution Overview
Problem
Existing hearing aid systems fail to optimize speech intelligibility and noise reduction for individual users in diverse sound environments, leading to suboptimal performance and user frustration, particularly for first-time users.
Innovation Solution
A hearing system that detects positive listening experiences using sound classifiers and neural networks to adapt signal processing characteristics, prompting users to report these experiences, and adjusts settings to enhance speech intelligibility and reduce noise, especially in nature and social environments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional hearing aid systems use fixed signal processing settings, then device complexity is reduced, but speech intelligibility and noise reduction performance deteriorate in diverse sound environments
Solution Approach 1:
The hearing aid system dynamically adapts its signal processing characteristics based on detected sound environments and user feedback. The system transitions from fixed settings to dynamic adjustment, modifying compression ratios, noise reduction levels, and other parameters in real-time to optimize speech intelligibility across diverse acoustic conditions.
Solution Approach 2:
The system incorporates feedback mechanisms where users report positive listening experiences, and this feedback is used to refine and update the hearing aid's signal processing settings. This closed-loop approach enables continuous improvement of performance based on actual user perception and listening conditions.
2Object-affected harmful factors
If hearing aid systems apply aggressive noise reduction algorithms, then noise reduction performance improves, but speech intelligibility and natural sound perception deteriorate
Solution Approach 1:
The system adjusts noise reduction parameters dynamically based on the detected sound environment and user feedback. Rather than applying aggressive noise reduction consistently, the system modulates compression ratios, threshold levels, and processing intensity to maintain an optimal balance between noise reduction and speech intelligibility across different acoustic contexts.
Solution Approach 2:
The noise reduction processing transitions from static to dynamic operation, adapting its aggressiveness level in real-time. The system monitors listening conditions and user responses to adjust the balance between noise suppression and speech clarity, preventing over-processing that would degrade natural sound perception.
3Reliability
If hearing aid systems use fixed compression ratios, then device complexity is reduced, but listening comfort and speech intelligibility deteriorate in varying sound levels
Solution Approach 1:
The compression ratio is transformed from a fixed parameter to a dynamically adjustable one. The system varies compression intensity based on detected sound levels, environmental conditions, and user feedback, ensuring optimal listening comfort across a wide dynamic range while maintaining speech intelligibility in varying acoustic conditions.
Solution Approach 2:
The hearing aid system performs self-adjustment of compression parameters based on automated environment detection and user feedback analysis. This self-service capability eliminates the need for manual reconfiguration by the user, allowing the system to autonomously optimize compression settings for different listening scenarios.
Data Source
AI summary
A hearing system includes at least one hearing aid. The hearing system is configured to detect a situation likely to invoke a positive listening experience and in response hereto prompting the hearing system user to report whether a positive listening experience has been encountered.