Hearing Device Feature Selection Using Sound Classification
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Solution Overview
Problem
Hearing device professionals and users face challenges in determining which features will be beneficial for an individual user, leading to difficulties in selecting suitable hearing devices and features, often resulting in unnecessary costs due to the lack of clear decision-making tools for feature usefulness.
Innovation Solution
A method that involves classifying input sound signals into various sound classes or signal types, logging usage quantities, determining relevant sound classes, identifying suitable hearing device features, and providing information to suggest or implement useful features, allowing for informed decisions on feature selection and optimization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If advanced hearing device features are provided to improve user benefit, then hearing capability and hearing experience are improved, but device cost increases
Solution Approach 1:
The system performs preliminary classification of sound signals and logging of usage quantities before the user makes a purchasing decision. By analyzing the user's actual hearing situations and feature usage patterns in advance, the system identifies which advanced features will provide the most benefit, allowing the user to make an informed decision about which expensive features are truly necessary for their specific needs.
Solution Approach 2:
The system changes the parameter of feature selection from subjective user preference to objective data-driven determination. By measuring actual usage quantities and classification results, the system transforms the decision-making process from based on user perception to based on measurable hearing situation data, identifying the optimal subset of features for each user.
2Adaptability or versatility
If comprehensive hearing device features are provided to cover all sound classes, then adaptability is improved, but device complexity increases
Solution Approach 1:
Instead of providing all possible features uniformly to all users, the system applies local quality by tailoring the feature set to each user's specific hearing situations. The classification of sound signals into different sound classes allows the system to identify which specific hearing situations the user encounters most frequently, and then provide only the features that are locally optimal for those specific situations rather than all features globally.
Solution Approach 2:
The system performs preliminary analysis of the user's hearing situations through sound classification and usage logging before determining the optimal feature set. This preliminary action identifies the user's specific needs across different sound classes, allowing the device to be configured with only the necessary features for those particular hearing situations rather than including all possible features.
3Loss of time
If users select features based on personal preference without objective data, then decision-making speed is improved, but feature usefulness decreases
Solution Approach 1:
The system implements feedback by providing users with objective information about their actual hearing situation patterns based on sound classification data and usage logging. This feedback loop allows users to see which sound classes they encounter most frequently and which features would be most useful for those specific situations, enabling faster and more reliable decision-making than subjective preference alone.
Solution Approach 2:
The system acts as an intermediary between the user's subjective preference and the objective reality of their hearing needs. By introducing the classification and usage analysis system as a mediator, it translates raw hearing situations into meaningful insights about feature usefulness, bridging the gap between what users think they need and what they actually need based on measured data.
Data Source
AI summary
The present invention proposes a method for determining hearing device features which are useful to an individual user of a hearing device (1). According to the proposed method a received input sound signal is automatically classified according to N sound classes. An overall usage quantity is then determined for each sound class from logged usage quantities of each sound class. Useful hearing device features are then determined, which are suitable for processing an input sound signal associated with sound classes having an overall usage quantity that exceeds a minimum overall usage quantity. Subsequently, providing the determined useful hearing device features in the hearing device (1) is suggested to the fitter and/or user of the hearing device (1). In a further aspect of the present invention a hearing device (1) with a classifier (7) and a logging unit (10) adapted to log usage quantities for identified sound classes is provided.