Adaptive environmental classification system for hearing aids
Keywords:
Cluster analysis, Feature extraction, Hearing aids, Learning systems, Merging, Adaptive environment, Adaptive learning process, Classification system, Merging environmentAbstract
An adaptive environmental classification system for hearing aids is introduced in which classes can be split and merged based on changes in the environment that the hearing aid is likely to encounter. The classification steps include information that distinguish different types of environments and the classification accuracy depending on the selection of features. The system stores the features in a buffer which is periodically processed to provide a single representative feature vector for the adaptive learning process. The adaptive learning phase begins when user fits the hearing aid and modifies the initial classification system to adapt to the user-specific environments. The general behavior of the adaptive classifier and the process of splitting and merging environment classes is represented by the squares in the center of each cluster represent the class centers.
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