Pre-Made Auditory Device Profiles Without Lengthy Hearing Tests
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Solution Overview
Problem
Hearing tests conducted by audiologists or applications are often time-consuming, and users may not complete them, leading to a delay in customizing auditory devices for their specific needs.
Innovation Solution
A computer-implemented method that allows users to provide preferences and select profiles through a user interface, utilizing machine-learning models to generate customized hearing profiles without requiring a traditional hearing test, and instructing auditory devices to implement these profiles.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If a traditional hearing test is conducted by an audiologist or application, then accurate hearing assessment is achieved, but the process becomes time-consuming and users may not complete it
Solution Approach 1:
The patent extracts the essential hearing assessment function from the traditional lengthy hearing test process. Instead of conducting a comprehensive clinical hearing test, the system uses a machine-learning model that processes user preferences and demographic information to generate hearing profiles, thereby achieving accurate hearing assessment without the time-consuming traditional test procedure
Solution Approach 2:
The patent creates simplified copies of hearing profiles based on user preferences and demographic data rather than requiring actual hearing test measurements. The machine-learning model generates these profile copies that approximate the results of traditional hearing tests, enabling quick assessment while maintaining reasonable accuracy
2Adaptability or versatility
If a traditional hearing test is required to customize auditory devices, then device customization is optimized, but user convenience deteriorates due to lengthy testing requirements
Solution Approach 1:
The patent enables users to self-generate their hearing profiles by simply providing preferences and demographic information through a user interface. The machine-learning model automatically processes this input and generates customized hearing profiles without requiring users to undergo professional hearing tests, thereby maintaining device customization capability while significantly improving ease of operation
Solution Approach 2:
The system performs preliminary hearing profile generation based on user preferences before the user actually needs the auditory device customized. By pre-processing user input through the machine-learning model to create hearing profiles, the system eliminates the need for time-consuming on-site hearing tests, thus maintaining customization quality while improving user convenience
Data Source
AI summary
A computer-implemented method includes downloading a hearing application. The method further includes providing a user interface that includes an option for a user associated with the user device to take a hearing test. The method further includes responsive to receiving a rejection of the option to take the hearing test, updating the user interface to include a list of user preferences. The method further includes receiving one or more user preferences from the user. The method further includes updating the user interface to include a set of profiles based on the one or more user preferences. The method further includes receiving a selection of a profile from the set of profiles. The method further includes instructing an auditory device to implement the selected profile.