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Automated machine learning based speech classification for hearing aid applications and its real-time implementation

Gautam Shreedhar Bhat, Nikhil Shankar, Issa M S Panahi

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
    |October 6, 2020
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces an automated machine learning (AutoML) voice activity detector (VAD) for smartphones, enhancing hearing aid performance in real-time. The efficient, low-delay model improves speech processing for hearing-impaired individuals.

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    Area of Science:

    • Audio signal processing
    • Machine learning applications
    • Hearing aid technology

    Background:

    • Deep neural networks (DNNs) have advanced audio processing, particularly for hearing aids.
    • Automated machine learning (AutoML) simplifies DNN model optimization for easier implementation.
    • Existing speech processing algorithms can be enhanced for improved speech perception.

    Purpose of the Study:

    • To develop an AutoML-based voice activity detector (VAD) for real-time smartphone application.
    • To improve speech processing in hearing aid devices through enhanced VAD.
    • To demonstrate the practical application of AutoML in hearing aid technology.

    Main Methods:

    • Utilized an AutoML platform to generate a computationally fast classification model.
    • Implemented the AutoML-generated VAD model on a smartphone for real-time operation.
    • Detailed the steps for real-time implementation on a mobile device.

    Main Results:

    • The AutoML-based VAD achieved computationally fast performance with minimal processing delay.
    • The real-time smartphone application demonstrated practical usability in various noisy environments.
    • Experimental results showed improvements over state-of-the-art techniques.

    Conclusions:

    • AutoML is a significant platform for developing efficient hearing aid applications.
    • The developed smartphone VAD app offers practical usability and enhances speech processing.
    • This work highlights the successful realization of an AutoML model on a smartphone for hearing aid applications.