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State-of-the-art hearing aids (HA) are limited in recognizing acoustic environments. Much effort is spent on research to improve listening experience for HA users in every acoustic situation. There is, however, no dedicated public database to train acoustic environment recognition algorithms with a specific focus on HA applications accounting for their requirements. Existing acoustic scene classification databases are inappropriate for HA signal processing.

With the strong growth of the mobile devices and emerging virtual reality (VR) and augmented reality (AR) applications, headsets are becoming more and more preferable in personal listening due to its convenience and portability. Assistive listening (AL) devices like hearing aids have seen much advancement. Creating a natural and authentic listening experience is the common objective of these VR, AR, and AL applications. In this tutorial, we will present state-of-the-art audio and acoustic signal processing techniques to enhance the sound reproduction in headsets and hearing aids.

This presentation deals with estimation of the target sound Direction of Arrival (DoA) for a Hearing Aid System (HAS) which can connect to a wireless microphone worn by a target talker. In this setup, the HAS is "informed" about the almost noise-free content of the target sound via the wireless microphone and can use this information for the DoA estimation. Here, we propose an "informed" DoA estimator based on the Time Difference of Arrival (TDoA) of the target sound at two microphones mounted on the ears of the HAS user---one microphone on each ear.