Hearing System Environment-Dependent Signal Processing
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Solution Overview
Problem
Current hearing systems struggle to accurately identify and adapt to individual environmental situations, relying on standardized definitions that may not fully represent a user's daily acoustic experiences, leading to suboptimal sound processing.
Innovation Solution
A method that determines environmental data features over multiple survey times, maps them into a representation space, and allows users to define specific signal processing settings for distinct environmental situations, enabling automatic adaptation of hearing system settings based on identified situations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If standardized listening situation definitions are used for hearing system operation, then the system can provide consistent signal processing settings, but the definitions may not accurately represent individual user's daily acoustic experiences
Solution Approach 1:
The system performs preliminary classification of acoustic environments into standardized listening situations before signal processing. By pre-defining listening situations with characteristic acoustic features, the system can quickly identify and apply appropriate signal processing settings without real-time complex analysis, ensuring consistency while covering individual user experiences through the comprehensive feature evaluation
Solution Approach 2:
The system changes multiple acoustic parameters simultaneously to characterize listening situations, including spectral features, temporal features, spatial features, and noise characteristics. By evaluating changes across these multiple parameters, the system can distinguish between different environmental situations and apply appropriate signal processing, balancing standardized operation with individual adaptability
2Measurement precision
If multiple acoustic features are evaluated to distinguish acoustic environments, then environmental identification accuracy improves, but the complexity of the identification process increases
Solution Approach 1:
The system segments the acoustic environment evaluation into distinct feature categories: spectral features, temporal features, spatial features, and noise characteristics. Each category is evaluated independently with specific algorithms, and the results are combined to form a comprehensive listening situation identification. This segmentation reduces overall complexity by making the evaluation process modular and manageable
Solution Approach 2:
The system introduces an intermediary classification layer that maps complex acoustic features to standardized listening situation categories. This intermediary layer simplifies the relationship between multiple acoustic measurements and signal processing settings, acting as a mediator that translates detailed environmental data into actionable processing parameters without requiring direct complex analysis of all features simultaneously
Data Source
AI summary
In a method for the environment-dependent operation of a hearing system values for a first plurality of environmental data of a first user of the hearing system are determined each time in a training phase for survey times, and the values of the environmental data for each of the survey times are used to form respectively a feature vector in an at least four-dimensional feature space. Each of the feature vectors is mapped respectively onto a corresponding representative vector in a maximum three-dimensional representation space, and a spatial distribution of a subgroup of representative vectors is used to define a first region in the representation space for a first environmental situation of the hearing system. A value of a setting for signal processing of the hearing system is specified for the first environmental situation, and the hearing system is operated with the value set in this way.