Research On Adaptive Environment Recognition System Of Digital Hearing Aids

Hearing aid,as a vital human hearing assistant device,has gone through the developmental stages from the vibration version,mechanical version,and automation version in the early stage to the smart version today.Currently,the using experience and hearing effect for human ears are more focused on for hearing-aid than ever,and it is possible to implement designs and applications corresponding to big data and artificial intelligence with their development.Based on deep learning,this paper proposed an artificial intelligent hearing aid through research.In traditional hearing system applications,the technologies chiefly used are the traditional digital signal processing technologies to conduct spectrum analysis,noise analysis,and so on.In this paper,the deep learning technology,database analysis technology,big data processing technology,and so on were applied in the research on the data and algorithm of hearing aid,and the designed hearing aid can automatically sense the surrounding environment and provide sound comfortable to human ears,equipped with improved using comfortability and functions such as noise canceling and directivity.In this paper,we conducted simple analysis of the development of hearing aid in and outside of China,proposed the research framework with analysis and organization,then learned the basic structure of hearing aid and the mathematical model of deep learning,and studied the advantages and reliability of this model in sound data processing.In the practices of this paper,the sound sensor was used to extract the sound perceivable by human ears,and the Python and corresponding artificial intelligence database were used to calculate and study the artificial intelligence system of the hearing aid,deeply combining the algorithm and data.In the end of this paper,with the algorithm and model remotely deployed on the cloud,and communication through 5G chips,tests were carried out for the designed system,verifying the feasibility of the technologies on human ear hearing aid.High-precision recognition was achieved in highly complex background,in smooth background,and under specific target,and the test algorithm score reached over 90%,presenting sufficient reliability of the algorithm.The research content in this paper is relatively comprehensive,including basic software applications,hardware test,and algorithm study,providing direction for future hearing aid application and artificial intelligence field research.