Signal Processing for Hearing Assistive Devices (2020)

Description:
Hearing assistive devices (HADs) are ubiquitous. They include, for example, devices such as headsets for speech communication in noisy environments (air plane crews, emergency/rescue teams, combat soldiers, police forces, etc.), headsets for offi ce use, gaming, etc., and hearing care systems, e.g. hearing aids and cochlear implants.

The course consists of lectures and hands-on exercises, which allow the course participants to understand in-depth the technical problems related to HADs and their potential solutions. The course has three main parts. The first part is an introductory part, which lays the foundation for the rest of the course, covering fundamental topics such as auditory perception (normal and impaired hearing) and a discussion of the basic principles of HADs. The second part provides an overview of fundamental signal processing problems encountered in HADs, and an in-depth treatment of state-of-the-art solutions. These include methods for beamforming and noise reduction, direction-of-arrival estimation, feedback and echo control, hearing loss compensation, etc. Furthermore, an overview is given of methodologies for evaluating HADs with a particular focus on methods for intelligibility assessment and estimation. The third part of the course presents emerging technologies for hearing assistive devices, including machine learning techniques for processing of speech in noise, audio-visual signal processing, user-aware/symbiotic signal processing, methods for own-voice processing, etc. While the course focuses on the HAD application, many of the discussed techniques are very general and find use in the much broader field of general sound processing. The course is multi-disciplinary, including topics such as basic auditory perception, statistical signal processing, deep learning, practical do’s and don’ts.

The course also bridges the gap between theoretical background and practical/robust application in practice. The course is a one-week concentrated course to be held in the Fall, 2020. The course involves course preparation (approximately 1 ECTS), course presence (1 ECTS), assignment finalization and hand-in (1 ECTS)

Prerequisites: Basic knowledge of statistical signal processing, stochastic processes, and linear algebra. Familiarity/handy with Matlab/Python.

Organizer: Professor Jesper Jensen

Lecturers: Prof. Jesper Jensen, AAU. Prof. Jan Østergaard, AAU. Prof. Zheng-Hua Tan, AAU. Dr. Meng Guo, Oticon (invited talk). Dr. Jan Mark de Haan, Sennheiser Comm. (invited talk). Dr.

Asger Heidemann Andersen, Oticon (invited talk). Dr. Svend Feldt, Sennheiser Comm. (invited talk). Dr. Carina Graversen, Eriksholm (invited talk).

ECTS: 3.0

Time: November 2020

Place: Aalborg University

Number of seats: 50

Deadline: 3 weeks prior to start

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.