Dear subscribers of the colloquium newsletter,
we are happy to inform you about the next dates of our Communication Technology Colloquium.
Wednesday, January 6, 2021
Speaker: Raphael Brandis
Time: 10:00 a.m.
Location: https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
Master Lecture: Personalized Occlusion Cancellation in Headphones and Hearing Aids
To users of headphones, hearables, and hearing aids, the occlusion effect (OE) is still a largely unsolved problem that causes them to perceive the sound of their own voice differently. In surveys, users commonly describe this OE-affected own-voice sound as hollow, boomy, and unpleasant. Other body-conducted sounds are affected as well; examples include the noise originating from footsteps or chewing.
A system that actively combats this effect has been in active development at the Institute of Communication Systems. This so-called Active Occlusion Cancellation (AOC) system is designed to cancel the average OE when applied to the average user’s occluded ear. Acoustic measurements as well as a listening test have shown it to be able to significantly reduce the OE and improve the users’ subjective experience. Unfortunately, both the OE and the acoustic characteristics of the occluded ear can vary significantly from user to user. That is why this thesis sets out to explore approaches to personalize the AOC system for individual users.
First, an objective scalar metric for the OE is proposed. This metric is then used to automatically adjust two scalar gains already present in the AOC system. These gains allow for a limited degree of personalization and, up until now, had to be adjusted manually. Second, a technique to iteratively design a personalized feedback controller based on a user’s acoustic measurements is introduced. This feedback controller is a major part of the AOC system. For the limited amount of user measurements that are available, this new design technique manages to quickly and reliably converge onto a controller that meets both the performance and robustness requirements. The controller design process is fully automated and does not require manual intervention by a control engineer. Finally, both personalization approaches are evaluated in a listening test of limited scope and size due to the ongoing COVID-19 pandemic.
and
Wednesday, January 6, 2021
Speaker: Ulrik Deneken
Time: 11:00 a.m.
Location: https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
Bachelor Lecture: Entwurf psychoakustisch optimierter signaladaptiver Übersprechkompensationsfilter
Für die Wiedergabe binauraler Signale über Lautsprecher muss das verwendete binaurale Signal vorgefiltert werden, damit der Höreindruck erhalten bleibt. Das Problem bei der Wiedergabe durch Lautsprechern ist, dass die Kanäle des Signales nicht mehr klar getrennt sind. Signalteile für das eine Ohr erreichen auch das andere Ohr. Dieses Problem wird als Übersprechen bezeichnet. Das Übersprechkompensationsfilter löst dieses Problem, indem die Signale über den Kreuzpfad entfernt werden und die Signale über den Direktpfad möglichst verzerrungsfrei wiedergegeben werden.
Mit Hilfe von psychoakustischer Maskierung soll in dieser Arbeit ein neuer Ansatz für die Entwicklung von Übersprechkompensationsfiltern gegeben werden. Das Signal des Kreuzpfades soll in diesem Ansatz nicht mehr vollständig verschwinden. Es würde ausreichen, wenn das Signal das Kreuzpfades unterhalb der Maskierungsschwelle des Signals des Direktpfades wäre. Hierzu wurden zwei Verfahren ausgearbeitet. Ein Verfahren beruft au fdem Ansatz einer konvexen Optimierung und wird im Frequenzbereich durchgeführt. Das andere Verfahren wird mittels nichtlinearer Nebenbedingungen im Zeitbereich gelöst.
Es konnte gezeigt werden, dass die Filter hinsichtlich der Maskierung verbessert werden können. Dies ist aber mit einem großen Rechenaufwand verbunden und hängt stark von dem verwendeten Eingangssignal ab. Die nichtsignaladaptiven Methoden liefern ein passables Ergebnis, jedoch konnte gezeigt werden, dass eine Verbesserung möglich ist.
All interested parties are cordially invited, registration is not required.
General information on the colloquium, as well as a current list of the dates of the Communication Technology Colloquium can be found at:
http://www.iks.rwth-aachen.de/aktuelles/kolloquium
--
Irina Ronkartz
Institute of Communication Systems (IKS)
RWTH Aachen University
Muffeter Weg 3a, 52074 Aachen, Germany
+49 241 80 26958 (phone)
ronkartz(a)iks.rwth-aachen.de
http://www.iks.rwth-aachen.de/
Dear subscribers of the colloquium newsletter,
we are happy to inform you about the next date of our Communication
Technology Colloquium.
*Tuesday, December 8, 2020*
*Speaker*: Hendrik Stelzer
*Time*: 10:00 a.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Bachelor Lecture*: Real-Time Use-Case Classification for Intelligent
Control of Hearables
A current goal in the development of headphones and hearables is that
users can wear theam at any time. Especially with the integration of
more and more features, specifically active noise cancellation (ANC) and
transparency features, a method of recognizing different acoustic
situations is necessary to enable intelligent control.
In this thesis an approach for intelligent classification of the current
wearing situation, or use case of headphones and hearing aids is
investigated. In addition to the simple recognition of whether the
earpiece is currently in use, the recognition of special cases such as
different fittings and closing the speaker outlet is examined. The
sensor signals used comprise one external and one internal microphone
signal for each side of the head. Real-time capable features are
extracted from the sensor signals and tested for their information
content regarding a use case classification. Based on headphone
simulations, a forward feature selection is conducted to find the set of
features enabling the most robust classification regardless of any kinds
of disturbane noise. The influence of both air conducted sound (ambient
noise) and body conducted sound (e.g. talking or chewing) is considered.
The mutual information is utilized to measure the quality of a feature.
Five well-known real-time capable classification methods are then
applied using the determined features and compared: the Fisher
discriminant, the least squares discriminant, logistic regression,
decision trees and Gaussian mixture models. Finally, the applicability
of the developed principles is verified by an implementation on a
real-time system (dSPACE ds1005)
All interested parties are cordially invited, registration is not required.
General information on the colloquium, as well as a current list of the
dates of the Communication Technology Colloquium can be found at:
http://www.iks.rwth-aachen.de/aktuelles/kolloquium/
--
Irina Ronkartz
Institute of Communication Systems (IKS)
RWTH Aachen University
Muffeter Weg 3a, 52074 Aachen, Germany
+49 241 80 26958 (phone)
ronkartz(a)iks.rwth-aachen.de
http://www.iks.rwth-aachen.de/