Hearing Aid Interference Identification Through Acoustic Feature Patterns
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Solution Overview
Problem
Identifying interference effects in hearing aids, such as wind noise, feedback, and reverberation, is difficult for users due to lack of technical knowledge and precise description, hindering effective compensation for hearing deficits.
Innovation Solution
A method and system that identifies interference effects through user-reported messages without detailed descriptions, using feature values to determine characteristic patterns and probabilities, employing artificial intelligence for accurate identification.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If detailed description of interference effect is required from user, then identification accuracy improves, but user burden and operation difficulty increase
Solution Approach 1:
The hearing aid system automatically collects feature values (acoustic environment, device settings, signal characteristics) and performs interference identification without requiring user description. The system serves itself by gathering necessary data through its existing sensors and processing chains, eliminating the burden of user intervention while maintaining accurate identification through objective measurements.
Solution Approach 2:
The patent replaces the manual description process (user verbally describing interference) with an automated electronic measurement and analysis system. The hearing aid's microphones, signal processors, and feature extraction algorithms substitute for human perception and communication, objectively capturing interference characteristics without relying on user terminology or knowledge.
2Ease of operation
If user provides subjective description of interference, then identification can proceed, but reliability decreases due to lack of technical knowledge
Solution Approach 1:
The patent replaces subjective user description with objective electronic measurements. The hearing aid system uses its microphones, signal processors, and feature extraction algorithms to objectively capture and analyze interference characteristics, replacing human perception and communication with electronic sensing and computational analysis for reliable identification.
Solution Approach 2:
The patent introduces an intermediary identification system that translates between the acoustic interference and the user's simple message. Rather than requiring direct user description of the interference, the system uses feature values as an intermediary representation that objectively characterizes the interference based on acoustic measurements and device state, bridging the gap between simple user input and reliable identification.
3Measurement precision
If multiple feature values are collected and analyzed, then identification accuracy improves, but processing complexity increases
Solution Approach 1:
The patent employs a universal identification approach where a single set of feature values serves multiple purposes: characterizing acoustic environment, detecting device state, and identifying interference type. The same microphones, signal processors, and analysis algorithms used for normal hearing aid function also perform interference identification, eliminating the need for separate dedicated systems and reducing overall complexity.
Data Source
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AI summary
A method for identifying a disturbance effect is described, wherein a hearing system (2) includes a hearing aid (4) worn by a user for sound output to the user, wherein the hearing system (2) is configured to repeatedly receive a message (M) from the user indicating that a disturbance effect is present during sound output, wherein, if the user reports a disturbance effect in a current situation, several features (F) of the current situation are determined and stored as a feature set (G), wherein an identification unit (20) compares several stored feature sets (G) with each other and thereby determines those features (F) which correspond in the several feature sets (G) and which are then assumed to be characteristic features (C) of the disturbance effect, such that the identification unit (20) identifies the disturbance effect based on the characteristic features (C).Furthermore, a hearing system (2) and a computer program product are specified.