Signal Processing Algorithms for Smartphone-Based Hearing Aid Platform; Applications and Clinical Testing




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Digital signal processing algorithms are widely utilized in hearing aid applications to im- prove the quality of speech. The signal processing pipeline for speech involves several crucial components that enhance hearing-impaired people’s listening. This thesis covers the devel- opment of novel methods that can be used in the speech processing pipeline and clinical testing. Each chapter of the dissertation focuses on the components of the speech process- ing pipeline for smartphone-based hearing aid setup. The first algorithm, speech source localization (SSL), which identifies the direction of the talker of interest using multiple mi- crophones, is discussed. A speaker identification method is proposed as an assistive system to the pipeline, and it can be used to boost the overall system’s performance. A clinical testing system is developed to evaluate the new signal processing algorithms. An approach is developed to use multiple microphones of iPhone simultaneously for real-time low-latency audio applications. Real-time integration of several signal processing modules that appear in digital hearing aids is developed as smartphone apps. Subjective evaluations are conducted for the proposed methods to show noticeable improvements and compared with state of the art methods. Additionally, the implementation of the proposed methods is explained on smartphones and computers.



Engineering, Electronics and Electrical