In-Ear Audio Seal Quality Adaptation for Occlusion and Noise
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Solution Overview
Problem
Active noise reduction systems in earpiece-based audio devices often fail to effectively address the occlusion effect, where users hear uncomfortable sounds due to a good earpiece seal, and struggle to maintain uniform performance across varying seal qualities.
Innovation Solution
A method and system that determine the seal quality of an earpiece-based audio device and switch between occlusion reduction and active noise reduction modes based on this quality, using internal and external microphones, a digital signal processor, and an accelerometer to improve voice clarity and reduce unwanted noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If the earpiece provides a good seal in the ear canal, then noise isolation is improved, but the occlusion effect increases causing uncomfortable sounds
Solution Approach 1:
The system dynamically switches between occlusion reduction mode and active noise reduction mode based on detected seal quality. When a good seal is detected, the system applies occlusion reduction processing to eliminate uncomfortable sounds. When seal quality is poor, the system switches to active noise reduction mode. This dynamic adaptation resolves the contradiction by adjusting the noise processing strategy based on actual seal conditions.
Solution Approach 2:
The system changes the processing parameters of acoustic signals based on seal quality determination. By analyzing acoustic signals from microphones and determining seal quality metrics, the system adjusts whether to apply occlusion reduction or active noise reduction algorithms, thereby optimizing performance across different seal conditions and resolving the trade-off between noise isolation and occlusion effect.
2Object-affected harmful factors
If active noise reduction is always applied, then unwanted noise is reduced, but performance becomes non-uniform across different seal qualities
Solution Approach 1:
The system dynamically adapts its noise reduction strategy based on real-time seal quality assessment. By continuously monitoring acoustic signals and determining seal quality, the system switches between different operational modes (occlusion reduction mode and active noise reduction mode) to maintain uniform performance across varying seal conditions, rather than applying a fixed noise reduction approach.
Solution Approach 2:
The system uses feedback from acoustic signal analysis to determine seal quality and adjust noise reduction processing accordingly. By analyzing signals from internal and external microphones, the system generates feedback about seal conditions and uses this information to select the appropriate noise reduction mode, ensuring reliable and uniform performance across different seal qualities.
3Loss of information
If occlusion reduction is always applied, then voice clarity is improved, but unwanted background noise is not effectively reduced
Solution Approach 1:
The system dynamically selects between occlusion reduction processing and active noise reduction processing based on determined seal quality. When a good seal is detected, occlusion reduction is applied to improve voice clarity by reducing the occlusion effect. When seal quality is poor, the system switches to active noise reduction to effectively reduce background noise. This dynamic selection ensures both voice clarity and noise reduction are optimized for the current seal condition.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
The system provides more uniform performance across different seal qualities, effectively reducing occlusion effects and unwanted noise, enhancing user experience by improving voice clarity and noise cancellation.
Implementation Method 1
an accelerometer to detect motion of the headset
Implementation Method 2
The anti-noise acoustic wave is intended to attenuate or eliminate the background noise at the listening position via a destructive interference
Implementation Method 3
The person may hear uncomfortable sounds from their own voice caused by bone-conducted sound reverberating off the earpiece blocking the ear canal
Data Source
AI summary
Systems and methods for active noise reduction and occlusion reduction based on seal quality of an in-the-ear (ITE) module inserted into a user's ear canal are provided. An example method includes receiving one or more acoustic signals. Each of the acoustic signals represents at least one captured sound having at least one of a voice component and an unwanted noise. The voice component may include the user's own voice. A quality of a seal of an ear canal is determined based at least partially on the acoustic signals. If the quality of the seal exceeds a predetermined threshold value, an occlusion reduction is performed on the acoustic signals to improve the voice component. If the quality of the seal is below a predetermined threshold value, active noise reduction is performed on the acoustic signals to reduce the unwanted noise.