Dear subscribers of the colloquium newsletter,
we are pleased to announce the next dates of our Communication
Technology Colloquium.
*Monday, July 19, 2021*
*Speaker:* Jonas Förster
*Time*: 2:30 p.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master-Lecture*: Multi-Channel Filter Design for Headphones with Active
Noise Cancelling
Active noise cancellation (ANC) headphones became increasingly popular
during the last decade. They are especially capable of reducing
low-frequent noise, where the passive isolation of headphones is
ineffective. Nowadays, commercial ANC headphones mostly use a single
reference microphone. This limits the maximum achievable active
attenuation. Adding multiple reference microphones to headphones can
overcome these limitations by exploiting the spatial characteristics of
the incoming noise.
This thesis presents two different multi-channel filter strategies for
feedforward ANC in headphones. On the one hand, a time-invariant filter
for reducing diffuse noise and on the other hand a time-variant filter
structure for reducing directional non-stationary noise are presented.
Additionally, a commercial ANC headphone is extended by multiple
reference microphones and the increase in active attenuation based on
the microphone positions is evaluated. The results indicate that both
filter techniques can improve the achievable active attenuation for
their dedicated use cases. Furthermore, the active attenuation can be
improved by additional microphones if they are placed on the side of the
corresponding loudspeaker.
and
*Monday, July 19, 2021*
*Speaker: *Zhi Li
*Time:* 3:15 p.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master-Lecture:* Real-Time Rendering of Recorded Spatial Audio Content
for Moving Listeners
All intersted parties are coridally invited, registration is not required.
General information about the colloquium as well as a current time scale
of the Communication Technology Colloquium can be found at:
https://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 pleased to announce the next date of our Communication Technology
Colloquium:
*Friday, July 9, 2021*
*Speaker:* Marc Mittag
*Time:* 3:30 p.m.
*Location*:
https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09
Meeting-ID: 979 0415 7921
Passwort: 481650
*Master-Lecture*: Deep Speech Inpainting for Masks Resulting from Noisy
Spectra
Speech enhancement belongs to the domain of noise detection, estimation
and reductionwith the goal of increasing speech quality and
intelligibility for speech signals subject toenvironmental noise.
However, conventional methods typically insufficiently remove noisein
challenging low-SNRnon-stationary noise environments.
In this thesis, we explore a twostage speech enhancement method
utilizing the strengths of machine learning and deep speechinpainting
for these difficult scenarios. Consisting out of a masking and
inpainting stage,we deploy two powerful residualCNNs in an
encoder-decoder structure, one for each stage.The purpose of the first
stage is to mask a noisy-speech magnitude spectrogram using
binarymasking such that it sufficiently removes noise but retains most
of the important speechinformation. The second stage deals with
reconstruction of the previously removedT-Fpointswith the goal of
creating a corruption-free, continuous clean-speech signal. The results
showthat our approach outperforms conventional speech enhancement
methods and achieves similarstate-of-the-art performance regarding other
speech inpainting studies. Compared to thenoisy-speech signal, our
approach achieves up to 3 times higherPESQscores and
substantialSNRimprovements of several decibels on ideal conditions.
Furthermore, we demonstrate thatthe inpainting neural network can
inpaint even highly masked speech if specifically trained for.
All interested parties are cordially invited, registration is not required.
General information about the colloquium as well as a current time scale
of the Communication Technology Colloquium can be found at:
https://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/