Dear subscribers of the colloquium newsletter,
we are happy to inform you about the next date of our Communication
Technology Colloquium.
*Thursday, December 3, 2020*
*Speaker*: Timothé Scheich
*Time*: 11:00 a.m.
*L**ocation*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Bachelor Lecture*: Methods for the Assessment of Headphones with Active
Noise Cancellation
Today, Active Noise Cancelling (ANC) headphones are a product daily used
by most people. How goog the headphones sound and how well their ANC is
working with respect to human perception, is still an open research
topic. Only few researchers have been studying the matter and provided
working measurement models. In this thesis, we first lay the groundwork
for a comprehensive understanding of already existing ANC headphones
assessment methods through an extensive research of related work.
Therewith, this thesis also motivates the importance of considering
psychoacoustic as an assessment tool by presenting several metrics
describing pleasantnes and annoyance of a sound. Furthermore, two
measurement series are conducted to gather ANC headphone performance
measurement data using several background noises. The measurement set-up
is explained, and the applied noise databases are presented. Later on,
we propose an assessment model using some of the described metrics.
Finally, we are able to highlight, by comparing the same type of on-ear
headphones, the importance of psychoacoustical parameters that may allow
differentiation of similarly performing objects. We conclude by
explaining the results and propose a subjective test to corroborate our
findings.
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, November 24, 2020*
*Speaker*: Fabian Malig
*Time*: 10:00 a.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Bachelor Lecture*: Robust Design of Adaptive ANC Systems Considering
Self-Induced Sound
In addition to passive attenuation, Active Noise Control (ANC) offers a
practical way to reduce the power of disturbing noise. Especially in
modern headphones this technology finds increasing popularity. Adaptive
filters promise a better ANC than time-variant filters since they adjust
to a changing environment. Though, they suffer from high sensitivity
towards noises caused by the user himself, like speaking or impact
sounds. Those noises are called self-induced sounds (SIS) in the following.
This thesis covers the Kalman-Filter as adaptive filter in a feedforward
ANC-system. It outperforms other adaptive algorithms concerning
different disturbances on the system, like self-induced sounds. The goal
of this thesis is the development of noise estimators and methods in
order to reduce the disturbing influence of self-induced sounds on
adaption.
All interested parties are cordially invited, registration is not required.
Generel information on the colloquium, as well as a current list of
dates of the Communication Technology Colloquium can be found at:
http://www.iks.rwth-aachen.de/atktuelles/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.
*Friday, November 20, 2020*
*Speaker*: Christian Schlaiß
*Time*: 2:00 p.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master Lecture*: Cancelling of Non-Stationary Disturbances in Active
Headphones
The occlusion effect is a consequence of sealing the ear canals with an
object such as a hearing aid or more generally a hearable. It results in
an amplification of lower frequencies and attenuation of higher
frequencies, which further leads to an unwanted distrotion of the
own-voice perception. To compensate this phenomenon, active and passive
solutions have been presented in literature. Passive solutions include
venting, where a ventilation hole is integrated into the hearing aid.
However, this leads to unwanted feedback. An active approch has been
presented by Liebich et al., in which a time-variant robust feedback
controller compensates the low frequency amplification. This solution is
limited to the attenuation of the occlusion effect on the own-voice.
Other body-conducted sounds, such as footsteps, chewing and swallowing
are not explicitly considered by Liebich et al.
In this thesis, body-conducted sounds exceeding the own voice components
are investigated and tackled. Measurements were conducted to identify
the spectral distribution of different BC sounds due to the occlusion
effect. Afterwards, a controller was designed to attenuate disturbances
in the region of 40 Hz to 80 Hz. This is followed by the introduction of
a stable controller interpolation scheme for switching between
controllers. By use of this so called Youla-Kucera interpolation method,
not only stability but also performance is guaranteed during switching
for a nominal path. Additionally, robust stability for this
interpolation scheme can be proven for discrete steps of delta and
additional constraints on the choice of Q. This is supplemented by a
simple and low complexity approach for detecting footsteps, based on
low-pass filter and recursive smoothing over time. Lastly, the
controller was implemented in real-time on a dSPACE ultra low latency
processing system to validate performance on the footsteps controller
and the switching performance. While the controller worked in theory,
real-time measurements revealed that additional tuning and possibly
additional sensors are needed for a better footsteps controller.
However, the switching scheme showed promising results, fading from one
controller to the other in a stable and smooth fashion. It also revealed
the possibility of real-time controller tuning with the help of the
interpolation coefficient. As all combinations of the two controllers
(with the interpolation coefficient 2) remain robust stable, switching
to different configurations is made possible.
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 dates of our Communication
Technology Colloquium.
*Wednesday, November 18, 2020*
*Speaker:* Leonie Geyer
*Time: *2:00 p.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master Lecture*: Sound Field Conversion Using Machine Learning Methods
The reproduction of realisitc sound fields is necessary for the
efficient evaluation of modern communication devices. Depending on the
application, different microphone arrangements are used to record the
sound fields. Not all desired signals are directly available in the
required microphone configuration. The goal of sound field conversion is
to convert any signal between different recording systems in an
identical sound field.
This thesis compares different approaches to convert sound fields. The
conversion between the signals of two concrete measurement systems, a
binaural artificial head and a microphone array with eight channel, is
investigated. Three new approaches, which use artificial neural
networks, are developed. First a convolutional approach, which has a
simple end-to-end structure. Secondly, a time filter approach. Here the
network outputs a FIR filter, which is applied to the input signal.
Third a variant of wavenet, which is divided into to subnetworks. One
analyses a section of the time signal and output a feature vector, which
is available to the conversion network when converting the time signal.
The neural networks are trained using data from real and defined
acoustic environments. The performance is measured by metrics in time
and frequency domain. As a comparison, sound field conversion by
equalising and measuring with the target recording device is performed.
Different experiments are conducted on the structure and
parametrisation, as well as the training process of the neural networks.
Their performance is observed and optimised. The Wavenet variant
achieves in all experiments the best results than the neural approaches.
Training with a loss function, which includes the mean square error and
frequency metrics, can reduce the error in the frequency domain,
although a higher error in the time domain is observed, compared to the
pure mean square error as loss function.
and
*Wednesday, November 18, 2020**
**Speaker:* Shahd Al Hares
*Time*: 3:00 p.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master Lecture*: Signal-Adaptive Approaches to Sound Field Translation
With the growing demands for spatial audio, Ambisonics became to attract
more attention in both fields of recording and reproduction of sound
field. Thus, the demand increased for applying sound field translation
that allows the use to move freely in different directions in the
acoustic scene. In Higher Order Ambisonics (HOA), the sound field
incidence is described in the reference point by a set of mathematical
functions known as Spherical Harmonics (SH). However, the reproduction
is restricted to the surrounding area of the reference point due to the
underlying recording hardware, which can be observed in the Ambisonics
domain as bandwidth limitation. In this thesis, an Ambisonics sound
field translation is investigated. Recent approaches were proposed that
allow the listener to move a few centimeters away from the reference
point (3DoF+). Another approach provides further translation of the
sound field (6DoF) but requires multiple Shperical Microphone Arrays
(SMA) to be used during the recording process.
In this thesis, an enhanced method for sound field translation is
proposed. It is based on upscaling the Higher Order Ambisonics (HOA)
signal to a higher SH order using Compressed Sensing (CS). CS is a
framework that is used to recover a signal from an under-determined
linear system. Different aspects of HOA upscaling and sound field
translation are studied theoretically and practically. Noise reduction
with CS for HOA signals is discussed, and the influence of source
distance on the translated signal is investigated in the
Near-Field-Compensated Higher Order Ambisonics (NFC-HOA) domain. A
systematic comparison between multiple translation approaches, namely
plane wave translation and space warping, is performed based on two
Monte Carlo experiments. Moreover, a new formulae is derived that
defines the limits of the upscaling SH order as a function of the
normalized translation distance and initial SH order. Finally, a method
is introduced for sound field translation of realistic signals based on
upscaling in frequency domain. The method is evaluated in frequency
domain for multiple Bark bands.
All interested parties are cordially invited, registration is not required.
General information on the colloquium, as well as 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.
*Monday, November 16, 2020**
**Speaker:* Lorenz Schmidt
*Time*: 11:00 a.m.
*Locatio**n*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master Lecture*: Noise Reduction Combining Conventional Approaches and
Artificial Neural Networks
The suppression of noise for single channel speech enhancement is one of
the most prominent challenges in signal processing and has been
addressed for decades. In recent years, the popularization of Machine
Learning algorithms and advances in deep neural network (DNN)
architectures have opened new perspectives and approaches to this field,
yielding impressive results. Many of these algorithms, however, require
a computational effort that exceeds the available resources of a
real-time application. One approach, called RNNoise, combines the
methods of classical signal processing with DNNs. Within a common noise
reduction architecture, a small weighting mask is sufficient to achieve
impressive results. The mask is estimated by a very small neural network
with a low computational complexity.
In this thesis, RNNoise is subject to several modifications that are
intended to improve its denoising performance, while maintaining its
affordable complexity. In a first step, the gated recurrent units (GRUs)
of the RNNoise architecture are replaced simple recurrent units (SRUs),
which improve its performance while speeding up the training process.
The DNN is expanded to estimate the pitch frequency, which is used in
the reconstruction of the harmonics with a comb filter. A new binary IIR
comb filter is developed and added to the signal processing of RNNoise.
Besides the modifications of RNNoise itself, a pitch estimator, based on
ordinary regression, and a mutual information metric are developed. The
evaluation shows a good performance for pitch estimation and voice
activity detection (VAD). A preliminary study analyzes the upper limits,
which can be achieved by the reduced spectral weighting mask. With bark
scaling, 22 gains are a reasonable tradeoff between performance and
complexity. Then, a theoretical evaluation shows that the new network
architecture improves the estimation considerably, especially in
non-stationary noise situations. A final evaluation compares a classical
noise suppression method, an end-to-end neural network approach,
classical RNNoise and the improved model by means of their cepstral
distances, speech-to-noise enhancement and perceptual measures. The
results show that the modifications give the new architecture an edge
over classical RNNoise. On the other hand, the developed IIR binary comb
filter falls back in the expectation and does not improve noise
suppression performance.
All interested parties are cordially invited, registration is not required.
General information on the colloquium, as well as a current list of
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, November 10, 2020*
*S**peaker: *Tom Deckenbrunnen
*Time:* 10:00 a.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Bachelor Lecture*: Significance-Aware Filtering for Nonlinear Acoustic
Echo Cancellation
The acoustic echoes arising in hands-free applications for mobile speech
communication contain considerable nonlinear distortions of the far-end
signal. Some causes of these nonlinearities include the progressive
miniaturization of components and the need for high play-back volume,
two opposing paradigm. It is therefore necessary to use methods of
nonlinear acoustic echo cancellation to provide sufficient quality of
communication. However, the limited resources in mobile devices render
many of these methods to alleviating the high computational complexity.
One approach to alleviating the high computational demand is the
so-called Significance-Aware filtering. Specifically, the cascaded
models based on parallel Significance-Aware decomposition of the system
identification task are treated in this thesis. The aim of this thesis
is the evaluation and enhancement of those structures. In particular,
methods for incorporating nonlinear memory into the parallel
Significance-Aware models are proposed. Beyond that, an analysis of the
necessary adaptation control for these structures is offered.
Results show that better performance can be achieved by the addition of
nonlinear memory to the parallel Significance-Aware models. It is
furthermore shown that the proposed enhancements solve a specific
problem of adaptation control. Nevertheless, adaptation control remains
a major point of interest for the parallel Significance-Aware models.
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/