Personalized Sound Management for Auditory Overload Filtering
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Solution Overview
Problem
The increasing diversity and intensity of background sounds lead to auditory overload, impacting health and safety as individuals struggle to distinguish important sounds from irrelevant noise, causing stress, sleeplessness, and potential hearing damage.
Innovation Solution
A personalized sound management system that uses devices with microphones and processors to identify sonic signatures, analyze sound pressure levels, and apply metadata and geocoding, allowing users to select and control sound applications that modify their acoustic environment, such as filtering out unwanted noise and enhancing important sounds.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If the brain processes all diverse background sounds, then complete auditory information is obtained, but auditory overload occurs impacting health and safety
Solution Approach 1:
The patent extracts and identifies specific sonic signatures (important sounds) from the mixed acoustic environment using Gaussian mixture models and pattern recognition. By separating important sounds from background noise through computational analysis, the system allows selective processing of only relevant auditory information, preventing auditory overload while maintaining completeness of important sound detection.
2Measurement precision
If background sound levels are reduced, then important sounds become easier to hear, but the system complexity increases
Solution Approach 1:
The patent introduces an intermediary computational layer (processor with Gaussian mixture models and pattern recognition algorithms) that mediates between the acoustic environment and human perception. This intermediary analyzes acoustic information, identifies sonic signatures, and selectively enhances or suppresses sounds, achieving improved sound detection accuracy without requiring complex physical sound modification hardware.
3Adaptability or versatility
If personalized sound management applications are made available, then user control over acoustic environment is improved, but the loss of time for application selection and setup increases
Solution Approach 1:
The patent implements self-service functionality where the system automatically performs sound analysis, identifies sonic signatures, and configures appropriate sound management settings without requiring extensive user input. The Gaussian mixture models and pattern recognition algorithms autonomously analyze the acoustic environment and apply suitable processing, reducing setup time while maintaining high adaptability through personalized sound profiles.
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
This system effectively reduces auditory overload by allowing users to customize their sound experience, improving hearing safety, reducing stress, and preventing hearing damage through intelligent noise management.
Implementation Method 1
a processor configured to identify sonic signatures where each sonic signature is identified using a Gaussian mixture model
Data Source
AI summary
A personalized sound management system for an acoustic space includes at least one transducer, a data communication system, one or more processors operatively coupled to the data communication system and the at least one transducer, and a medium coupled to the one or more processors. The processors access a database of sonic signatures and display a plurality of personalized sound management applications that perform at least one or more tasks among identifying a sonic signature, calculating a sound pressure level, storing metadata related to a sonic signature, monitoring sound pressure level dosage levels, switching to an ear canal microphone in a noisy environment, recording a user's voice, storing the user's voice in a memory of an earpiece device, or storing the user's voice in a memory of a server system, or converting received text received in texts or emails to voice using text to speech conversion. Other embodiments are disclosed.