Hearing Aid Sound Classification Using Hierarchical Segmentation
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Solution Overview
Problem
Existing hearing aid systems face challenges in providing precise and robust sound classification using minimal processing resources, which can lead to deteriorated sound quality and speech intelligibility due to complex and resource-intensive classification methods.
Innovation Solution
A hearing aid system that employs a sound environment classifier with a feature extractor providing Mel Frequency Cepstral Coefficients, modulation cepstrum coefficients, and tonality features, using a band-pass filter bank with non-linearly spaced frequency bands and a classifier comprising a base class and final class classifier to efficiently classify sound environments with reduced processing requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If complex sound classification methods are used to improve sound environment identification accuracy, then measurement precision is improved, but device complexity increases and processing resources are consumed
Solution Approach 1:
The sound environment classification system is segmented into multiple hierarchical levels: a first level with multiple base classes (including music class) and a second level with more specific sound environment classes. This segmentation allows the system to achieve high classification accuracy by progressively narrowing down from broad categories to specific environments, while keeping each individual classification stage relatively simple and computationally efficient.
Solution Approach 2:
The patent introduces a hierarchical dimension to the classification system, organizing sound environments in multiple levels from general to specific. This dimensional approach transforms a potentially complex single-level classification problem into a series of simpler multi-level decisions, improving accuracy without proportionally increasing overall system complexity.
2Measurement precision
If complex sound classification methods are used to improve sound environment identification accuracy, then measurement precision is improved, but processing resources are consumed
Solution Approach 1:
By segmenting the classification into hierarchical levels where the music class is identified at an intermediate stage, the system avoids the computational burden of processing all possible sound environment categories simultaneously. This segmentation enables efficient resource usage by focusing processing power on distinguishing music from other environments before proceeding to more specific classifications.
Solution Approach 2:
The system performs preliminary classification into base classes including music before proceeding to final sound environment classification. This preliminary action of identifying music early in the hierarchy allows subsequent processing to be optimized or simplified, reducing overall processing resource consumption while maintaining high accuracy in music environment detection.
3Device complexity
If simple classification methods are used to reduce processing resources, then device complexity is reduced, but measurement precision deteriorates
Solution Approach 1:
The hierarchical segmentation allows each classification level to remain relatively simple in structure while collectively achieving high precision. By dividing the classification task into manageable stages with clear decision boundaries, the system maintains low complexity at each step while the cumulative effect of multiple stages delivers high overall classification accuracy for sound environments including music.
4Use of energy by moving object
If simple classification methods are used to reduce processing resources, then processing resources are conserved, but measurement precision deteriorates
Solution Approach 1:
The preliminary classification into base classes serves as an efficient filtering stage that consumes minimal processing resources while providing valuable information for subsequent classification. This preliminary action of grouping sound environments into broader categories first allows the system to achieve high final classification accuracy without the computational expense of analyzing all detailed categories simultaneously, thus conserving processing resources.
Data Source
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AI summary
A method of operating a hearing aid system (400) based on a classification of the current sound environment, which includes a measure of a beat probability and a hearing aid system for carrying out such a method.