Welcome to CASPR Summer School on Signal Processing for Hearing Assistive Devices (2021)

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 office 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 is multi-disciplinary, with a focus on application of theoretical results to real-world problems, and practical do's and don'ts.

The course has three main parts. The first part is a short 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, voice activity detection, feedback 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, intelligibility prediction, 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 general and find use in the much broader field of general sound processing.

The course also bridges the gap between theoretical background and practical/robust application. The course is a one-week concentrated course to be held in the Summer, 2021. 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.

The course schedule is still under preparation.

Course Fee: Free for PhD students and postdocs. The fee is 7500 DKK (1000 EUR) for industrial participants.

For more information about the Summer School, feel free to contact the organizers:
Prof. Jesper Jensen (jje@es.aau.dk), Prof. Zheng-Hua Tan (zt@es.aau.dk), and Prof. Jan Østergaard (jo@es.aau.dk).

The course will be given following the guidelines of the Danish Health Authorities on the COVID-19, and will take place with physical presence of (and physical distance between) the course participants. In case the Covid-19 situation prevent us from having physical presence, an alternative online version of the course will be introduced.

Organizer: Professor Jesper Jensen - jje@es.aau.dk

Lecturers: Prof. Jesper Jensen, AAU, Prof. Jan Østergaard, AAU.
Prof. Zheng-Hua Tan, AAU., Dr. Meng Guo, Oticon (invited talk), Dr. Asger Heidemann Andersen, Oticon (invited talk), Dr. Carina Graversen, Eriksholm (invited talk), Poul Hoang (AAU), Payam Shahsavari (AAU), Dr. Daniel Michelsanti (AAU), Dr. Iván López Espejo

ECTS: 3.0 

Time: 17-21 May 2021

Place: Aalborg University, Fredrik Bajers Vej 7b, 9220 Aalborg, Denmark.

Zip code: 

City: Aalborg

Number of seats: 30

Deadline: 26 April 2021

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.