Workshop: School on Hearing Acoustics: Models, Machine Learning, Applications, and Virtual Reality - Details

Workshop: School on Hearing Acoustics: Models, Machine Learning, Applications, and Virtual Reality - Details

General information

Course name Workshop: School on Hearing Acoustics: Models, Machine Learning, Applications, and Virtual Reality
Subtitle
Semester WiSe22/23
Current number of participants 16
Home institute Graduate School Science, Medicine and Technology (Oltech)
Associated institutions Department of Medical Physics and Accoustics
Courses type Workshop in category Teaching
First date Monday, 13.03.23, 08:30 - 17:00 o'clock W30
Type/Form Workshop
Participants Master students and doctoral students from the auditory sciences
Lehrsprache englisch
ECTS points 1

Rooms and times

W30

  • Monday, 13.03.23, 08:30 - 17:00 o'clock
  • Tuesday, 14.03.23, 08:30 - 12:00 o'clock

Comment/Description

The Winter School provides a great opportunity for Master and PhD students to broaden their understanding in several fields required in cutting-edge hearing research. It will give insights into the current research addressed in the collaborative research centre (CRC) "Hearing Acoustics" (www.hearing-acoustics.de) dedicated to advance our understanding of auditory perception in complex acoustic environments (CAEs) and to improve acoustic communication in such difficult environments.

Apart from tutorial talks on research topics of the CRC, hands-on exercises will be offered to gain experience with modern tools (e.g., auditory models, immersive hearing device, binaural localization algorithms, room acoustics software) that have been developed or applied within the CRC for creating, assessing and analyzing communication situations in virtual CAEs with and without hearing supportive algorithms/devices.

Admission settings

The course is part of admission "Anmeldung gesperrt (global)".
Erzeugt durch den Stud.IP-Support
The following rules apply for the admission:
  • Admission locked.

Registration mode

After enrolment, participants will manually be selected.

Potential participants are given additional information before enroling to the course.