Kommunikationstechnik-Kolloquium

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September 2020

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Kommunikationstechnisches Kolloquium am IKS | Communication Technology Colloquium at IKS
by Irina Ronkartz 22 Sep '20

22 Sep '20

-- English version below -- Sehr geehrte Abonnenten des Kolloquium-Newsletters, gerne informieren wir Sie über den nächsten Termin unseres Kommunikationstechnischen Kolloquiums. *Montag, 28. September 2020* *Vortragender:* Zach Lee *Zeit:* 11:00 Uhr *Ort*: https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09 Meeting-ID: 979 0415 7921 Passwort: 481650 *Bachelor-Vortrag*: Time-Varying Simulation of Adaptive Crosstalk Cancellation Systems based on Acoustic Measurements In order to reproduce binaural audio via loudspeakers, a crosstalk cancellation (CTC) system is necessary to attenuate the crosstalk. The task is becoming more challenging when the listener is allowed to move, as the CTC system is often robust in a small and limited area. A recent innovative idea known as the adaptive crosstalk cancellation (ACTC) system is proposed. The CTC filter in this system is updated real-time by placing mircophones close to the entrance of the ear canal to measure the signals perceived by the listener and estimate the corresponding head-related impulse response (HRIR). The goal of this thesis is to evaluate the ACTC system by performing an acoustic measurement in an anechoic chamber to obtain the real and accurate HRIR of the test listener. With this knowledge, the performance of the ACTC system can be evaluated in a simulation. Furthermore, the limit of the ACTC system can be tested, in terms of how fast it can adapt to changes. The results show that the ACTC system has a fairly good performance when the listener's ears are on the ipsilateral side of the loudspeakers and the performance falls drastically on the contralateral side. In lower frequencies, the ACTC system works quite well up to a movement (head rotation) speed of 20 deg/s. Alle Interessierten sind herzlich eingeladen, eine Anmeldung ist nicht erforderlich. Allgemeine Informationen zum Kolloquium sowie eine aktuelle Liste der Termine des Kommunikationstechnischen Kolloquiums finden Sie unter: http://www.iks.rwth-aachen.de/aktuelles/kolloquium Dear subscirbers of the colloquium newsletter, we are happy to inform you about the next date of our communication technology colloquium. *Monday, September 28, 2020* *Speaker*: Zach Lee *Time:* 11:00 a.m. *Location*: https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09 Meeting-ID: 979 0415 7921 Passwort: 481650 *Bachelor Lecture*: Time-Varying Simulation of Adaptive Crosstalk Cancellation Systems based on Acoustic Measurements In order to reproduce binaural audio via loudspeakers, a crosstalk cancellation (CTC) system is necessary to attenuate the crosstalk. The task is becoming more challenging when the listener is allowed to move, as the CTC system is often robust in a small and limited area. A recent innovative idea known as the adaptive crosstalk cancellation (ACTC) system is proposed. The CTC filter in this system is updated real-time by placing microphones close to the entrance of the ear canal to measure the signals perceibed by the listener and estimate the corresponding head-related impulse response (HRIR). The goal of this thesis is to evaluate the ACTC system by performing an acoustic measurement in an anechoic chamber to obtain the real and accurate HRIR of the test listener. With this knowledge, the performance of the ACTC system can be evaluated in a simulation. Furthermore, the limit of the ACTC system can be tested, in terms of how fast it can adapt to changes. The results show that the ACTC system has a fairly good performance when the listener's ears are on the ipsilateral side of the loudspeakers and the performance falls drastically on the contralateral side. In lower frequencies, the ACTC system works quite well up to a movement (head rotation) speed of 20 deg/s. 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/aktulles/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/

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Kommunikationstechnisches Kolloquium am IKS | Communication Technology Colloquium at IKS
by Irina Ronkartz 18 Sep '20

18 Sep '20

--- Englich version below --- Sehr geehrte Abonnenten des Kolloquium-Newsletters, gerne informieren wir Sie über den nächsten Termin unseres Kommunikationstechnischen Kolloquiums. *Freitag, 25. September 2020* *Vortr**agende*: Liuhui Deng *Zeit*: 11:00 Uhr *Ort*: https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09 Meeting-ID: 979 0415 7921 Passwort: 481650 *Master-Vortrag*: Speech Inpainting Using Image Processing Techniques Speech inpainting is a task that reconstructs speech from damaged speech signals, wherein corruption can result from improper storage, packet loss in communication networks and etc. Neural networks are becoming an active research hot-spot in the field of audio inpainting in recent years, including speech inpainting, music inpainting and etc. The networks can either be fed waveforms of audio or other feature representations such as Short-Time Frequency Transform (STFT), Mel Frequency Cepstral Coefficients (MFCC) and etc. in order to reconstruct audio. In this thesis, advanced Convolutional Neural Networks (CNNs) based architectures in image inpainting are adopted to the task speech inpainting. The motivation lie in the facts that the neural techniques in image inpainting are well investigated and turn out to be powerful, besides, the task speech inpainting can be interpreted as image inpainting when speech spectrogram is treated as 2-dimensional image. The involving networks are mainly context encoder, context encoder with Generative Adversarial Networks (GANs), EdgeConnect (w / o GANs) and EdgeConnect (with GANs). In this work, context encoder is an encoder decoder architecture and takes as input STFT magnitudes (and ground truth corruption mask) while EdgeConnect is fed additionally edge map of spectrogram in order to alleviate the blurriness issue observed in image inpainting. EdgeConnect (w / o GANs) is composed of two sub-models, both of which are a context encoder. One sub-model is referred to as edge completion model which reconstructs edge map from corrupted edge map and the other is inpainting model which reconstructs spectrogram based on correupted spectrogram and edge map. GANs applied in the models of interest are also intended to mitigate the blurriness by adding adversarial loss from GANs to the loss function of context encoder, edge completion model and inpainting model. Experiments indicate that context encoder (w/ or w/o GANs) outperforms the CNNs which are simply stacking a few convolutional layers. EdgeConnect (w/ or w/o GANs) achieves even better performance than context encoder (w/ or w/o GANs) mainly thanks to additional informative edge map of spectrogram. The best model among them is EdgeConnect (with GANs), its reconstructed speeches achieve 3,03 in terms of PESQ score, 71,2% improvement compared to input corrupted speech. Besides, analyses of edge map quality in EdgeConnect (w/ or w/o GANs) reveal that edge map of low quality heavily degrades the inpainting performance, thus a well performing edge completion model is of great importance and is a promising direction to put more effort into in the future. Alle Interessierten sind herzlich eingeladen, eine Anmeldung ist nicht erforderlich. Allgemeine Informationen zum Kolloquium sowie eine aktuelle Liste der Termine des Kommunikationstechnischen Kolloquiums finden Sie unter: http://www.iks.rwth-aachen.de/aktuelles/kolloquium/ Dear subscribers of the colloquium newsletter, we are happy to inform you about the next date of our communication technology colloquium. *Friday, September 25, 2020* *Speaker*: Liuhui Deng *Time*: 11:00 a.m. *Location*: https://rwth.zoom.us/j/97904157921?pwd=SWpsbDl0MWhrWjY1ZkZaeFRoYmErZz09 Meeting-ID: 979 0415 7921 Passwort: 481650 *Master Lecture*: Speech Inpainting Using Image Processing Techniques Speech inpainting is a task that reconstructs speech from damaged speech signals, wherein corruption can result from improper storage, packet loss in communication networks and etc. Neural networks are becoming an active research hot-spot in the field of audio inpainting in recent years, including speech inpainting, music inpainting and etc. The networks can either be fed waveforms of audio or other feature representations such as Short-Time Frequency Transform (STFT), Mel Frequency Cepstral Coefficients (MFCC) and etc. in order to reconstruct audio. In this thesis, advanced Convolutional Neural Networks (CNNs) based architectures in image inpainting are adopted to the task speech inpainting. The motivation lie in the facts that the neural techniques in image inpainting are well investigated and turn out to be powerful, besides, the task speech inpainting can be interpreted as image inpainting when speech spectrogram is treated as 2-dimensional image. The involving networks are mainly context encoder, context encoder with Generative Adversarial Networks (GANs), EdgeConnect (w / o GANs) and EdgeConnect (with GANs). In this work, context encoder is an encoder decoder architecture and takes as input STFT magnitudes (and ground truth corruption mask) while EdgeConnect is fed additionally edge map of spectrogram in order to alleviate the blurriness issue observed in image inpainting. EdgeConnect (w / o GANs) is composed of two sub-models, both of which are a context encoder. One sub-model is referred to as edge completion model which reconstructs edge map from corrupted edge map and the other is inpainting model which reconstructs spectrogram based on correupted spectrogram and edge map. GANs applied in the models of interest are also intended to mitigate the blurriness by adding adversarial loss from GANs to the loss function of context encoder, edge completion model and inpainting model. Experiments indicate that context encoder (w/ or w/o GANs) outperforms the CNNs which are simply stacking a few convolutional layers. EdgeConnect (w/ or w/o GANs) achieves even better performance than context encoder (w/ or w/o GANs) mainly thanks to additional informative edge map of spectrogram. The best model among them is EdgeConnect (with GANs), its reconstructed speeches achieve 3,03 in terms of PESQ score, 71,2% improvement compared to input corrupted speech. Besides, analyses of edge map quality in EdgeConnect (w/ or w/o GANs) reveal that edge map of low quality heavily degrades the inpainting performance, thus a well performing edge completion model is of great importance and is a promising direction to put more effort into in the future. 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/

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