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Vol Th4A.6. ; 2018.","bibtex":"@inproceedings{Kress_Gudyriev_Zwickel_Kemal_Lischke_Zimmermann_Koos_Scheytt_2018, title={64 GBd Monolithically Integrated Coherent QPSK Single Polarization Receiver in 0.25 µm SiGe-Photonic Technology}, volume={Th4A.6}, booktitle={Optical Fiber Communication Conference 2018, San Diego}, author={Kress, Christian and Gudyriev, Sergiy and Zwickel, Heiner and Kemal, Juned N. and Lischke, Stefan and Zimmermann, Lars and Koos, Christian and Scheytt, Christoph}, year={2018} }","mla":"Kress, Christian, et al. “64 GBd Monolithically Integrated Coherent QPSK Single Polarization Receiver in 0.25 Μm SiGe-Photonic Technology.” <i>Optical Fiber Communication Conference 2018, San Diego</i>, vol. Th4A.6, 2018.","short":"C. Kress, S. Gudyriev, H. Zwickel, J.N. Kemal, S. Lischke, L. Zimmermann, C. Koos, C. Scheytt, in: Optical Fiber Communication Conference 2018, San Diego, 2018.","chicago":"Kress, Christian, Sergiy Gudyriev, Heiner Zwickel, Juned N. Kemal, Stefan Lischke, Lars Zimmermann, Christian Koos, and Christoph Scheytt. “64 GBd Monolithically Integrated Coherent QPSK Single Polarization Receiver in 0.25 Μm SiGe-Photonic Technology.” In <i>Optical Fiber Communication Conference 2018, San Diego</i>, Vol. Th4A.6, 2018.","apa":"Kress, C., Gudyriev, S., Zwickel, H., Kemal, J. N., Lischke, S., Zimmermann, L., Koos, C., &#38; Scheytt, C. (2018). 64 GBd Monolithically Integrated Coherent QPSK Single Polarization Receiver in 0.25 µm SiGe-Photonic Technology. <i>Optical Fiber Communication Conference 2018, San Diego</i>, <i>Th4A.6</i>.","ieee":"C. Kress <i>et al.</i>, “64 GBd Monolithically Integrated Coherent QPSK Single Polarization Receiver in 0.25 µm SiGe-Photonic Technology,” in <i>Optical Fiber Communication Conference 2018, San Diego</i>, San Diego, CA, USA , 2018, vol. 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Electronic Photonic Integrated Circuits for Coherent and Non-Coherent Receivers. In: <i>10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)</i>. IEEE; 2018.","bibtex":"@inproceedings{Gudyriev_Kress_Scheytt_2018, place={Germany/Aachen}, title={Electronic Photonic Integrated Circuits for Coherent and Non-Coherent Receivers}, booktitle={10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)}, publisher={IEEE}, author={Gudyriev, Sergiy and Kress, Christian and Scheytt, Christoph}, year={2018} }","apa":"Gudyriev, S., Kress, C., &#38; Scheytt, C. (2018). Electronic Photonic Integrated Circuits for Coherent and Non-Coherent Receivers. <i>10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)</i>.","ieee":"S. Gudyriev, C. Kress, and C. Scheytt, “Electronic Photonic Integrated Circuits for Coherent and Non-Coherent Receivers,” 2018.","short":"S. Gudyriev, C. Kress, C. 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Scheytt, in: 10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018), IEEE, Germany/Aachen, 2018.","chicago":"Scheytt, Christoph. “Ultra‐broadband Signal Processing by Means of Electronic‐Photonic Integration.” In <i>10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)</i>. Germany/Aachen: IEEE, 2018.","ieee":"C. Scheytt, “Ultra‐broadband Signal Processing by means of Electronic‐Photonic Integration,” 2018.","apa":"Scheytt, C. (2018). Ultra‐broadband Signal Processing by means of Electronic‐Photonic Integration. <i>10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)</i>.","bibtex":"@inproceedings{Scheytt_2018, place={Germany/Aachen}, title={Ultra‐broadband Signal Processing by means of Electronic‐Photonic Integration}, booktitle={10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)}, publisher={IEEE}, author={Scheytt, Christoph}, year={2018} }","ama":"Scheytt C. Ultra‐broadband Signal Processing by means of Electronic‐Photonic Integration. In: <i>10th Sino-German Joint Symposium on Opto- and Microelectronic Devices and Circuits (SODC 2018)</i>. 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ESPnet mainly focuses on end-to-end automatic speech recognition (ASR), and adopts widely-used dynamic neural network toolkits, Chainer and Py-Torch, as a main deep learning engine. ESPnet also follows the Kaldi ASR toolkit style for data processing, feature extraction/format, and recipes to provide a complete setup for speech recognition and other speech processing experiments. This paper explains a major architecture of this software platform, several important functionalities, which differentiate ESPnet from other open source ASR toolkits, and experimental results with\r\nmajor ASR benchmarks.","lang":"eng"}],"file":[{"content_type":"application/pdf","file_id":"29954","file_size":288907,"access_level":"open_access","file_name":"INTERSPEECH_2018_Heymann_Paper.pdf","date_updated":"2022-02-23T08:03:13Z","relation":"main_file","date_created":"2022-02-23T08:03:13Z","creator":"huesera"}],"date_created":"2022-02-21T10:34:37Z","type":"conference","department":[{"_id":"54"}],"year":"2018","title":"ESPnet: End-to-End Speech Processing Toolkit","author":[{"full_name":"Watanabe, Shinji","last_name":"Watanabe","first_name":"Shinji"},{"full_name":"Hori, Takaaki","first_name":"Takaaki","last_name":"Hori"},{"last_name":"Karita","first_name":"Shigeki","full_name":"Karita, Shigeki"},{"full_name":"Hayashi, Tomoki","first_name":"Tomoki","last_name":"Hayashi"},{"full_name":"Nishitoba, Jiro","last_name":"Nishitoba","first_name":"Jiro"},{"first_name":"Yuya","last_name":"Unno","full_name":"Unno, Yuya"},{"full_name":"Enrique Yalta Soplin, Nelson","last_name":"Enrique Yalta Soplin","first_name":"Nelson"},{"id":"9168","full_name":"Heymann, Jahn","first_name":"Jahn","last_name":"Heymann"},{"full_name":"Wiesner, Matthew","first_name":"Matthew","last_name":"Wiesner"},{"last_name":"Chen","first_name":"Nanxin","full_name":"Chen, Nanxin"},{"full_name":"Renduchintala, Adithya","first_name":"Adithya","last_name":"Renduchintala"},{"first_name":"Tsubasa","last_name":"Ochiai","full_name":"Ochiai, Tsubasa"}],"date_updated":"2023-01-11T11:23:19Z","language":[{"iso":"eng"}],"doi":"10.21437/Interspeech.2018-1456","file_date_updated":"2022-02-23T08:03:13Z","citation":{"apa":"Watanabe, S., Hori, T., Karita, S., Hayashi, T., Nishitoba, J., Unno, Y., Enrique Yalta Soplin, N., Heymann, J., Wiesner, M., Chen, N., Renduchintala, A., &#38; Ochiai, T. (2018). ESPnet: End-to-End Speech Processing Toolkit. <i>INTERSPEECH 2018, Hyderabad, India</i>, 2207–2211. <a href=\"https://doi.org/10.21437/Interspeech.2018-1456\">https://doi.org/10.21437/Interspeech.2018-1456</a>","mla":"Watanabe, Shinji, et al. “ESPnet: End-to-End Speech Processing Toolkit.” <i>INTERSPEECH 2018, Hyderabad, India</i>, 2018, pp. 2207–2211, doi:<a href=\"https://doi.org/10.21437/Interspeech.2018-1456\">10.21437/Interspeech.2018-1456</a>.","ieee":"S. Watanabe <i>et al.</i>, “ESPnet: End-to-End Speech Processing Toolkit,” in <i>INTERSPEECH 2018, Hyderabad, India</i>, 2018, pp. 2207–2211, doi: <a href=\"https://doi.org/10.21437/Interspeech.2018-1456\">10.21437/Interspeech.2018-1456</a>.","chicago":"Watanabe, Shinji, Takaaki Hori, Shigeki Karita, Tomoki Hayashi, Jiro Nishitoba, Yuya Unno, Nelson Enrique Yalta Soplin, et al. “ESPnet: End-to-End Speech Processing Toolkit.” In <i>INTERSPEECH 2018, Hyderabad, India</i>, 2207–2211, 2018. <a href=\"https://doi.org/10.21437/Interspeech.2018-1456\">https://doi.org/10.21437/Interspeech.2018-1456</a>.","short":"S. Watanabe, T. Hori, S. Karita, T. Hayashi, J. Nishitoba, Y. Unno, N. Enrique Yalta Soplin, J. Heymann, M. Wiesner, N. Chen, A. Renduchintala, T. Ochiai, in: INTERSPEECH 2018, Hyderabad, India, 2018, pp. 2207–2211.","ama":"Watanabe S, Hori T, Karita S, et al. ESPnet: End-to-End Speech Processing Toolkit. In: <i>INTERSPEECH 2018, Hyderabad, India</i>. ; 2018:2207–2211. doi:<a href=\"https://doi.org/10.21437/Interspeech.2018-1456\">10.21437/Interspeech.2018-1456</a>","bibtex":"@inproceedings{Watanabe_Hori_Karita_Hayashi_Nishitoba_Unno_Enrique Yalta Soplin_Heymann_Wiesner_Chen_et al._2018, title={ESPnet: End-to-End Speech Processing Toolkit}, DOI={<a href=\"https://doi.org/10.21437/Interspeech.2018-1456\">10.21437/Interspeech.2018-1456</a>}, booktitle={INTERSPEECH 2018, Hyderabad, India}, author={Watanabe, Shinji and Hori, Takaaki and Karita, Shigeki and Hayashi, Tomoki and Nishitoba, Jiro and Unno, Yuya and Enrique Yalta Soplin, Nelson and Heymann, Jahn and Wiesner, Matthew and Chen, Nanxin and et al.}, year={2018}, pages={2207–2211} }"},"oa":"1","status":"public","has_accepted_license":"1","page":"2207–2211","_id":"29923","ddc":["000"],"user_id":"59789"},{"citation":{"mla":"Habernal, Ivan, et al. “The Argument Reasoning Comprehension Task: Identification and            Reconstruction of Implicit Warrants.” <i>Proceedings of the 2018 Conference of the North American Chapter of          the Association for Computational Linguistics: Human Language          Technologies, Volume 1 (Long Papers)</i>, Association for Computational Linguistics, 2018, doi:<a href=\"https://doi.org/10.18653/v1/n18-1175\">10.18653/v1/n18-1175</a>.","bibtex":"@inproceedings{Habernal_Wachsmuth_Gurevych_Stein_2018, title={The Argument Reasoning Comprehension Task: Identification and            Reconstruction of Implicit Warrants}, DOI={<a href=\"https://doi.org/10.18653/v1/n18-1175\">10.18653/v1/n18-1175</a>}, booktitle={Proceedings of the 2018 Conference of the North American Chapter of          the Association for Computational Linguistics: Human Language          Technologies, Volume 1 (Long Papers)}, publisher={Association for Computational Linguistics}, author={Habernal, Ivan and Wachsmuth, Henning and Gurevych, Iryna and Stein, Benno}, year={2018} }","ama":"Habernal I, Wachsmuth H, Gurevych I, Stein B. 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Association for Computational Linguistics; 2018. doi:<a href=\"https://doi.org/10.18653/v1/n18-1036\">10.18653/v1/n18-1036</a>","mla":"Habernal, Ivan, et al. “Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies            in Web Argumentation.” <i>Proceedings of the 2018 Conference of the North American Chapter of          the Association for Computational Linguistics: Human Language          Technologies, Volume 1 (Long Papers)</i>, Association for Computational Linguistics, 2018, doi:<a href=\"https://doi.org/10.18653/v1/n18-1036\">10.18653/v1/n18-1036</a>."},"type":"conference","department":[{"_id":"34"},{"_id":"820"}],"date_created":"2023-10-19T08:29:28Z","date_updated":"2023-10-19T12:09:55Z","publication_status":"published","title":"Before Name-Calling: Dynamics and Triggers of Ad Hominem Fallacies            in Web Argumentation","year":"2018","status":"public","author":[{"full_name":"Habernal, Ivan","first_name":"Ivan","last_name":"Habernal","id":"101881"},{"last_name":"Wachsmuth","first_name":"Henning","full_name":"Wachsmuth, Henning"},{"full_name":"Gurevych, Iryna","last_name":"Gurevych","first_name":"Iryna"},{"full_name":"Stein, Benno","first_name":"Benno","last_name":"Stein"}],"doi":"10.18653/v1/n18-1036","user_id":"15504","publisher":"Association for Computational Linguistics","_id":"48302","language":[{"iso":"eng"}]},{"type":"conference","department":[{"_id":"34"},{"_id":"820"}],"date_created":"2023-10-19T08:29:58Z","publication":"Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing","citation":{"mla":"Daxenberger, Johannes, et al. “What Is the Essence of a Claim? Cross-Domain Claim Identification.” <i>Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing</i>, Association for Computational Linguistics, 2018, doi:<a href=\"https://doi.org/10.18653/v1/d17-1218\">10.18653/v1/d17-1218</a>.","ama":"Daxenberger J, Eger S, Habernal I, Stab C, Gurevych I. What is the Essence of a Claim? Cross-Domain Claim Identification. In: <i>Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing</i>. Association for Computational Linguistics; 2018. doi:<a href=\"https://doi.org/10.18653/v1/d17-1218\">10.18653/v1/d17-1218</a>","bibtex":"@inproceedings{Daxenberger_Eger_Habernal_Stab_Gurevych_2018, title={What is the Essence of a Claim? Cross-Domain Claim Identification}, DOI={<a href=\"https://doi.org/10.18653/v1/d17-1218\">10.18653/v1/d17-1218</a>}, booktitle={Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing}, publisher={Association for Computational Linguistics}, author={Daxenberger, Johannes and Eger, Steffen and Habernal, Ivan and Stab, Christian and Gurevych, Iryna}, year={2018} }","apa":"Daxenberger, J., Eger, S., Habernal, I., Stab, C., &#38; Gurevych, I. (2018). What is the Essence of a Claim? Cross-Domain Claim Identification. <i>Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing</i>. <a href=\"https://doi.org/10.18653/v1/d17-1218\">https://doi.org/10.18653/v1/d17-1218</a>","ieee":"J. Daxenberger, S. Eger, I. Habernal, C. Stab, and I. Gurevych, “What is the Essence of a Claim? Cross-Domain Claim Identification,” 2018, doi: <a href=\"https://doi.org/10.18653/v1/d17-1218\">10.18653/v1/d17-1218</a>.","short":"J. Daxenberger, S. Eger, I. Habernal, C. Stab, I. Gurevych, in: Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing, Association for Computational Linguistics, 2018.","chicago":"Daxenberger, Johannes, Steffen Eger, Ivan Habernal, Christian Stab, and Iryna Gurevych. “What Is the Essence of a Claim? Cross-Domain Claim Identification.” In <i>Proceedings of the 2017 Conference on Empirical Methods in Natural          Language Processing</i>. Association for Computational Linguistics, 2018. <a href=\"https://doi.org/10.18653/v1/d17-1218\">https://doi.org/10.18653/v1/d17-1218</a>."},"doi":"10.18653/v1/d17-1218","user_id":"15504","_id":"48304","publisher":"Association for Computational Linguistics","language":[{"iso":"eng"}],"date_updated":"2023-10-19T12:08:19Z","publication_status":"published","status":"public","year":"2018","title":"What is the Essence of a Claim? Cross-Domain Claim Identification","author":[{"last_name":"Daxenberger","first_name":"Johannes","full_name":"Daxenberger, Johannes"},{"first_name":"Steffen","last_name":"Eger","full_name":"Eger, Steffen"},{"full_name":"Habernal, Ivan","last_name":"Habernal","first_name":"Ivan","id":"101881"},{"full_name":"Stab, Christian","first_name":"Christian","last_name":"Stab"},{"first_name":"Iryna","last_name":"Gurevych","full_name":"Gurevych, Iryna"}]},{"_id":"12899","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/INTERSPEECH_2018_Heitkaemper_Paper.pdf","open_access":"1"}],"user_id":"460","author":[{"id":"40767","full_name":"Boeddeker, Christoph","first_name":"Christoph","last_name":"Boeddeker"},{"full_name":"Heitkaemper, Jens","first_name":"Jens","last_name":"Heitkaemper","id":"27643"},{"full_name":"Schmalenstroeer, Joerg","first_name":"Joerg","last_name":"Schmalenstroeer","id":"460"},{"id":"11213","full_name":"Drude, Lukas","last_name":"Drude","first_name":"Lukas"},{"full_name":"Heymann, Jahn","first_name":"Jahn","last_name":"Heymann"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"year":"2018","title":"Front-End Processing for the CHiME-5 Dinner Party Scenario","status":"public","date_updated":"2023-10-26T08:14:15Z","date_created":"2019-07-30T14:35:15Z","department":[{"_id":"54"}],"oa":"1","type":"conference","citation":{"ama":"Boeddeker C, Heitkaemper J, Schmalenstroeer J, Drude L, Heymann J, Haeb-Umbach R. Front-End Processing for the CHiME-5 Dinner Party Scenario. In: <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>. ; 2018.","bibtex":"@inproceedings{Boeddeker_Heitkaemper_Schmalenstroeer_Drude_Heymann_Haeb-Umbach_2018, title={Front-End Processing for the CHiME-5 Dinner Party Scenario}, booktitle={Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India}, author={Boeddeker, Christoph and Heitkaemper, Jens and Schmalenstroeer, Joerg and Drude, Lukas and Heymann, Jahn and Haeb-Umbach, Reinhold}, year={2018} }","mla":"Boeddeker, Christoph, et al. “Front-End Processing for the CHiME-5 Dinner Party Scenario.” <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>, 2018.","chicago":"Boeddeker, Christoph, Jens Heitkaemper, Joerg Schmalenstroeer, Lukas Drude, Jahn Heymann, and Reinhold Haeb-Umbach. “Front-End Processing for the CHiME-5 Dinner Party Scenario.” In <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>, 2018.","short":"C. Boeddeker, J. Heitkaemper, J. Schmalenstroeer, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India, 2018.","apa":"Boeddeker, C., Heitkaemper, J., Schmalenstroeer, J., Drude, L., Heymann, J., &#38; Haeb-Umbach, R. (2018). Front-End Processing for the CHiME-5 Dinner Party Scenario. <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>.","ieee":"C. Boeddeker, J. Heitkaemper, J. Schmalenstroeer, L. Drude, J. Heymann, and R. Haeb-Umbach, “Front-End Processing for the CHiME-5 Dinner Party Scenario,” 2018."},"publication":"Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India","project":[{"name":"Computing Resources Provided by the Paderborn Center for Parallel Computing","_id":"52"}],"abstract":[{"text":"This contribution presents a speech enhancement system for the CHiME-5 Dinner Party Scenario. The front-end employs multi-channel linear time-variant filtering and achieves its gains without the use of a neural network. We present an adaptation of blind source separation techniques to the CHiME-5 database which we call Guided Source Separation (GSS). Using the baseline acoustic and language model, the combination of Weighted Prediction Error based dereverberation, guided source separation, and beamforming reduces the WER by 10:54% (relative) for the single array track and by 21:12% (relative) on the multiple array track.","lang":"eng"}],"quality_controlled":"1","related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/INTERSPEECH_2018_Heitkaemper_Poster.pdf","relation":"supplementary_material","description":"Poster"}]}},{"project":[{"name":"Akustische Sensornetzwerke - Teilprojekt ","_id":"27"},{"name":"Akustische Sensornetzwerke - Teilprojekt \"Verteilte akustische Signalverarbeitung über funkbasierte Sensornetzwerke","_id":"27"}],"abstract":[{"lang":"eng","text":"Signal processing in WASNs is based on a software framework for hosting the algorithms as well as on a set of wireless connected devices representing the hardware. Each of the nodes contributes memory, processing power, communication bandwidth and some sensor information for the tasks to be solved on the network. \r\nIn this paper we present our MARVELO framework for distributed signal processing. It is intended for transforming existing centralized implementations into distributed versions. To this end, the software only needs a block-oriented implementation, which MARVELO picks-up and distributes on the network. Additionally, our sensor node hardware and the audio interfaces responsible for multi-channel recordings are presented."}],"quality_controlled":"1","citation":{"mla":"Afifi, Haitham, et al. “MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks.” <i>Speech Communication; 13th ITG-Symposium</i>, 2018, pp. 1–5.","bibtex":"@inproceedings{Afifi_Schmalenstroeer_Ullmann_Haeb-Umbach_Karl_2018, title={MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks}, booktitle={Speech Communication; 13th ITG-Symposium}, author={Afifi, Haitham and Schmalenstroeer, Joerg and Ullmann, Joerg and Haeb-Umbach, Reinhold and Karl, Holger}, year={2018}, pages={1–5} }","ama":"Afifi H, Schmalenstroeer J, Ullmann J, Haeb-Umbach R, Karl H. MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks. In: <i>Speech Communication; 13th ITG-Symposium</i>. ; 2018:1-5.","ieee":"H. Afifi, J. Schmalenstroeer, J. Ullmann, R. Haeb-Umbach, and H. Karl, “MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks,” in <i>Speech Communication; 13th ITG-Symposium</i>, 2018, pp. 1–5.","apa":"Afifi, H., Schmalenstroeer, J., Ullmann, J., Haeb-Umbach, R., &#38; Karl, H. (2018). MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks. <i>Speech Communication; 13th ITG-Symposium</i>, 1–5.","short":"H. Afifi, J. Schmalenstroeer, J. Ullmann, R. Haeb-Umbach, H. Karl, in: Speech Communication; 13th ITG-Symposium, 2018, pp. 1–5.","chicago":"Afifi, Haitham, Joerg Schmalenstroeer, Joerg Ullmann, Reinhold Haeb-Umbach, and Holger Karl. “MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks.” In <i>Speech Communication; 13th ITG-Symposium</i>, 1–5, 2018."},"publication":"Speech Communication; 13th ITG-Symposium","department":[{"_id":"75"},{"_id":"54"}],"type":"conference","date_created":"2019-01-17T15:47:35Z","date_updated":"2023-10-26T08:15:32Z","author":[{"id":"65718","last_name":"Afifi","first_name":"Haitham","full_name":"Afifi, Haitham"},{"id":"460","full_name":"Schmalenstroeer, Joerg","last_name":"Schmalenstroeer","first_name":"Joerg"},{"full_name":"Ullmann, Joerg","first_name":"Joerg","last_name":"Ullmann","id":"16256"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"},{"full_name":"Karl, Holger","last_name":"Karl","first_name":"Holger","id":"126"}],"status":"public","year":"2018","title":"MARVELO - A Framework for Signal Processing in Wireless Acoustic Sensor Networks","user_id":"460","_id":"6859","language":[{"iso":"eng"}],"page":"1-5"},{"citation":{"apa":"Grimm, C., Breddermann, T., Farhoud, R., Fei, T., Warsitz, E., &#38; Haeb-Umbach, R. (2018). Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar. <i>International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018</i>.","ieee":"C. Grimm, T. Breddermann, R. Farhoud, T. Fei, E. Warsitz, and R. Haeb-Umbach, “Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar,” 2018.","short":"C. Grimm, T. Breddermann, R. Farhoud, T. Fei, E. Warsitz, R. Haeb-Umbach, in: International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018, 2018.","chicago":"Grimm, Christopher, Tobias Breddermann, Ridha Farhoud, Tai Fei, Ernst Warsitz, and Reinhold Haeb-Umbach. “Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar.” In <i>International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018</i>, 2018.","mla":"Grimm, Christopher, et al. “Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar.” <i>International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018</i>, 2018.","ama":"Grimm C, Breddermann T, Farhoud R, Fei T, Warsitz E, Haeb-Umbach R. Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar. In: <i>International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018</i>. ; 2018.","bibtex":"@inproceedings{Grimm_Breddermann_Farhoud_Fei_Warsitz_Haeb-Umbach_2018, title={Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar}, booktitle={International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018}, author={Grimm, Christopher and Breddermann, Tobias and Farhoud, Ridha and Fei, Tai and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2018} }"},"publication":"International Conference on Microwaves for Intelligent Mobility (ICMIM) 2018","abstract":[{"text":"In this paper, we present a neural network based classification algorithm for the discrimination of moving from stationary targets in the sight of an automotive radar sensor. Compared to existing algorithms, the proposed algorithm can take into account multiple local radar targets instead of performing classification inference on each target individually resulting in superior discrimination accuracy, especially suitable for non rigid objects, like pedestrians, which in general have a wide velocity spread when multiple targets are detected.","lang":"eng"}],"quality_controlled":"1","date_created":"2019-07-12T05:27:29Z","oa":"1","department":[{"_id":"54"}],"type":"conference","author":[{"last_name":"Grimm","first_name":"Christopher","full_name":"Grimm, Christopher"},{"full_name":"Breddermann, Tobias","last_name":"Breddermann","first_name":"Tobias"},{"last_name":"Farhoud","first_name":"Ridha","full_name":"Farhoud, Ridha"},{"last_name":"Fei","first_name":"Tai","full_name":"Fei, Tai"},{"first_name":"Ernst","last_name":"Warsitz","full_name":"Warsitz, Ernst"},{"last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"status":"public","year":"2018","title":"Discrimination of Stationary from Moving Targets with Recurrent Neural Networks in Automotive Radar","date_updated":"2023-11-20T16:37:39Z","language":[{"iso":"eng"}],"_id":"11747","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ICMIM_2018_Haeb-Umbach_Paper.pdf"}],"user_id":"242"},{"quality_controlled":"1","related_material":{"link":[{"description":"Slides","url":"https://groups.uni-paderborn.de/nt/pubs/2018/INTERSPEECH_2018_Glarner_Slides.pdf","relation":"supplementary_material"}]},"abstract":[{"text":"The invention of the Variational Autoencoder enables the application of Neural Networks to a wide range of tasks in unsupervised learning, including the field of Acoustic Unit Discovery (AUD). The recently proposed Hidden Markov Model Variational Autoencoder (HMMVAE) allows a joint training of a neural network based feature extractor and a structured prior for the latent space given by a Hidden Markov Model. It has been shown that the HMMVAE significantly outperforms pure GMM-HMM based systems on the AUD task. However, the HMMVAE cannot autonomously infer the number of acoustic units and thus relies on the GMM-HMM system for initialization. This paper introduces the Bayesian Hidden Markov Model Variational Autoencoder (BHMMVAE) which solves these issues by embedding the HMMVAE in a Bayesian framework with a Dirichlet Process Prior for the distribution of the acoustic units, and diagonal or full-covariance Gaussians as emission distributions. Experiments on TIMIT and Xitsonga show that the BHMMVAE is able to autonomously infer a reasonable number of acoustic units, can be initialized without supervision by a GMM-HMM system, achieves computationally efficient stochastic variational inference by using natural gradient descent, and, additionally, improves the AUD performance over the HMMVAE.","lang":"eng"}],"publication":"INTERSPEECH 2018, Hyderabad, India","citation":{"mla":"Glarner, Thomas, et al. “Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery.” <i>INTERSPEECH 2018, Hyderabad, India</i>, 2018.","bibtex":"@inproceedings{Glarner_Hanebrink_Ebbers_Haeb-Umbach_2018, title={Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery}, booktitle={INTERSPEECH 2018, Hyderabad, India}, author={Glarner, Thomas and Hanebrink, Patrick and Ebbers, Janek and Haeb-Umbach, Reinhold}, year={2018} }","ama":"Glarner T, Hanebrink P, Ebbers J, Haeb-Umbach R. Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. In: <i>INTERSPEECH 2018, Hyderabad, India</i>. ; 2018.","ieee":"T. Glarner, P. Hanebrink, J. Ebbers, and R. Haeb-Umbach, “Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery,” 2018.","apa":"Glarner, T., Hanebrink, P., Ebbers, J., &#38; Haeb-Umbach, R. (2018). Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery. <i>INTERSPEECH 2018, Hyderabad, India</i>.","short":"T. Glarner, P. Hanebrink, J. Ebbers, R. Haeb-Umbach, in: INTERSPEECH 2018, Hyderabad, India, 2018.","chicago":"Glarner, Thomas, Patrick Hanebrink, Janek Ebbers, and Reinhold Haeb-Umbach. “Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery.” In <i>INTERSPEECH 2018, Hyderabad, India</i>, 2018."},"type":"conference","department":[{"_id":"54"}],"oa":"1","date_created":"2019-07-12T05:30:34Z","date_updated":"2023-11-22T08:29:22Z","title":"Full Bayesian Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery","status":"public","year":"2018","author":[{"first_name":"Thomas","last_name":"Glarner","full_name":"Glarner, Thomas","id":"14169"},{"first_name":"Patrick","last_name":"Hanebrink","full_name":"Hanebrink, Patrick"},{"id":"34851","full_name":"Ebbers, Janek","first_name":"Janek","last_name":"Ebbers"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"user_id":"34851","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2018/INTERSPEECH_2018_Glarner_Paper.pdf"}],"_id":"11907","language":[{"iso":"eng"}]},{"author":[{"first_name":"J.E.","last_name":"van Engelen","full_name":"van Engelen, J.E."},{"last_name":"van Lier","first_name":"J.J.","full_name":"van Lier, J.J."},{"full_name":"Takes, F.W.","first_name":"F.W.","last_name":"Takes"},{"full_name":"Trautmann, Heike","first_name":"Heike","orcid":"0000-0002-9788-8282","last_name":"Trautmann","id":"100740"}],"year":"2018","status":"public","title":"Accurate WiFi based indoor positioning with continuous location sampling","date_updated":"2023-10-16T13:33:18Z","language":[{"iso":"eng"}],"_id":"46350","publisher":"Springer","page":"524–540","user_id":"15504","citation":{"chicago":"Engelen, J.E. van, J.J. van Lier, F.W. Takes, and Heike Trautmann. “Accurate WiFi Based Indoor Positioning with Continuous Location Sampling.” In <i>Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)</i>, 524–540. Dublin, Ireland: Springer, 2018.","short":"J.E. van Engelen, J.J. van Lier, F.W. Takes, H. Trautmann, in: Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD), Springer, Dublin, Ireland, 2018, pp. 524–540.","apa":"van Engelen, J. E., van Lier, J. J., Takes, F. W., &#38; Trautmann, H. (2018). Accurate WiFi based indoor positioning with continuous location sampling. <i>Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)</i>, 524–540.","ieee":"J. E. van Engelen, J. J. van Lier, F. W. Takes, and H. Trautmann, “Accurate WiFi based indoor positioning with continuous location sampling,” in <i>Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)</i>, 2018, pp. 524–540.","ama":"van Engelen JE, van Lier JJ, Takes FW, Trautmann H. Accurate WiFi based indoor positioning with continuous location sampling. In: <i>Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)</i>. Springer; 2018:524–540.","bibtex":"@inproceedings{van Engelen_van Lier_Takes_Trautmann_2018, place={Dublin, Ireland}, title={Accurate WiFi based indoor positioning with continuous location sampling}, booktitle={Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)}, publisher={Springer}, author={van Engelen, J.E. and van Lier, J.J. and Takes, F.W. and Trautmann, Heike}, year={2018}, pages={524–540} }","mla":"van Engelen, J. E., et al. “Accurate WiFi Based Indoor Positioning with Continuous Location Sampling.” <i>Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)</i>, Springer, 2018, pp. 524–540."},"publication":"Proceedings of the European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Database (ECML/PKDD)","abstract":[{"lang":"eng","text":"The ubiquity of WiFi access points and the sharp increase in WiFi-enabled devices carried by humans have paved the way for WiFi-based indoor positioning and location analysis. Locating people in indoor environments has numerous applications in robotics, crowd control, indoor facility optimization, and automated environment mapping. However, existing WiFi-based positioning systems suffer from two major problems: (1) their accuracy and precision is limited due to inherent noise induced by indoor obstacles, and (2) they only occasionally provide location estimates, namely when a WiFi-equipped device emits a signal. To mitigate these two issues, we propose a novel Gaussian process (GP) model for WiFi signal strength measurements. It allows for simultaneous smoothing (increasing accuracy and precision of estimators) and interpolation (enabling continuous sampling of location estimates). Furthermore, simple and efficient smoothing methods for location estimates are introduced to improve localization performance in real-time settings. Experiments are conducted on two data sets from a large real-world commercial indoor retail environment. Results demonstrate that our approach provides significant improvements in terms of precision and accuracy with respect to unfiltered data. Ultimately, the GP model realizes continuous location sampling with consistently high quality location estimates."}],"place":"Dublin, Ireland","date_created":"2023-08-04T07:54:43Z","department":[{"_id":"34"},{"_id":"819"}],"type":"conference"},{"volume":14,"doi":"10.1016/j.bdr.2018.05.005","user_id":"15504","_id":"46351","language":[{"iso":"eng"}],"page":"101–111","intvolume":"        14","date_updated":"2023-10-16T13:33:43Z","author":[{"last_name":"Carnein","first_name":"Matthias","full_name":"Carnein, Matthias"},{"full_name":"Trautmann, Heike","last_name":"Trautmann","orcid":"0000-0002-9788-8282","first_name":"Heike","id":"100740"}],"year":"2018","title":"evoStream — Evolutionary Stream Clustering Utilizing Idle Times","status":"public","department":[{"_id":"34"},{"_id":"819"}],"type":"journal_article","date_created":"2023-08-04T07:55:33Z","abstract":[{"lang":"eng","text":"Clustering is an important field in data mining that aims to reveal hidden patterns in data sets. It is widely popular in marketing or medical applications and used to identify groups of similar objects. Clustering possibly unbounded and evolving data streams is of particular interest due to the widespread deployment of large and fast data sources such as sensors. The vast majority of stream clustering algorithms employ a two-phase approach where the stream is first summarized in an online phase. Upon request, an offline phase reclusters the aggregations into the final clusters. In this setup, the online component will idle and wait for the next observation in times where the stream is slow. This paper proposes a new stream clustering algorithm called evoStream which performs evolutionary optimization in the idle times of the online phase to incrementally build and refine the final clusters. Since the online phase would idle otherwise, our approach does not reduce the processing speed while effectively removing the computational overhead of the offline phase. In extensive experiments on real data streams we show that the proposed algorithm allows to output clusters of high quality at any time within the stream without the need for additional computational resources."}],"citation":{"mla":"Carnein, Matthias, and Heike Trautmann. “EvoStream — Evolutionary Stream Clustering Utilizing Idle Times.” <i>Big Data Research</i>, vol. 14, 2018, pp. 101–111, doi:<a href=\"https://doi.org/10.1016/j.bdr.2018.05.005\">10.1016/j.bdr.2018.05.005</a>.","ama":"Carnein M, Trautmann H. evoStream — Evolutionary Stream Clustering Utilizing Idle Times. <i>Big Data Research</i>. 2018;14:101–111. doi:<a href=\"https://doi.org/10.1016/j.bdr.2018.05.005\">10.1016/j.bdr.2018.05.005</a>","bibtex":"@article{Carnein_Trautmann_2018, title={evoStream — Evolutionary Stream Clustering Utilizing Idle Times}, volume={14}, DOI={<a href=\"https://doi.org/10.1016/j.bdr.2018.05.005\">10.1016/j.bdr.2018.05.005</a>}, journal={Big Data Research}, author={Carnein, Matthias and Trautmann, Heike}, year={2018}, pages={101–111} }","apa":"Carnein, M., &#38; Trautmann, H. (2018). evoStream — Evolutionary Stream Clustering Utilizing Idle Times. <i>Big Data Research</i>, <i>14</i>, 101–111. <a href=\"https://doi.org/10.1016/j.bdr.2018.05.005\">https://doi.org/10.1016/j.bdr.2018.05.005</a>","ieee":"M. Carnein and H. Trautmann, “evoStream — Evolutionary Stream Clustering Utilizing Idle Times,” <i>Big Data Research</i>, vol. 14, pp. 101–111, 2018, doi: <a href=\"https://doi.org/10.1016/j.bdr.2018.05.005\">10.1016/j.bdr.2018.05.005</a>.","short":"M. Carnein, H. Trautmann, Big Data Research 14 (2018) 101–111.","chicago":"Carnein, Matthias, and Heike Trautmann. “EvoStream — Evolutionary Stream Clustering Utilizing Idle Times.” <i>Big Data Research</i> 14 (2018): 101–111. <a href=\"https://doi.org/10.1016/j.bdr.2018.05.005\">https://doi.org/10.1016/j.bdr.2018.05.005</a>."},"publication":"Big Data Research"},{"date_updated":"2023-10-16T13:34:21Z","intvolume":"        40","status":"public","title":"Multiobjective evolutionary algorithms based on target region preferences","year":"2018","author":[{"full_name":"Li, L","first_name":"L","last_name":"Li"},{"full_name":"Wang, Y","first_name":"Y","last_name":"Wang"},{"id":"100740","last_name":"Trautmann","first_name":"Heike","orcid":"0000-0002-9788-8282","full_name":"Trautmann, Heike"},{"full_name":"Jing, N","first_name":"N","last_name":"Jing"},{"last_name":"Emmerich","first_name":"M","full_name":"Emmerich, M"}],"doi":"10.1016/j.swevo.2018.02.006","user_id":"15504","volume":40,"page":"196–215","language":[{"iso":"eng"}],"_id":"46353","abstract":[{"text":"Incorporating decision makers' preferences is of great significance in multiobjective optimization. Target region-based multiobjective evolutionary algorithms (TMOEAs), aiming at a well-distributed subset of Pareto optimal solutions within the user-provided region(s), are extensively investigated in this paper. An empirical comparison is performed among three TMOEA instantiations: T-NSGA-II, T-SMS-EMOA and T-R2-EMOA. Experimental results show that T-SMS-EMOA has the best overall performance regarding the hypervolume indicator within the target region, while T-NSGA-II is the fastest algorithm. We also compare TMOEAs with other state-of-the-art preference-based approaches, i.e., DF-SMS-EMOA, RVEA, AS-EMOA and R-NSGA-II to show the advantages of TMOEAs. A case study in the mission planning of earth observation satellite is carried out to verify the capabilities of TMOEAs in the real-world application. Experimental results indicate that preferences can improve the searching ability of MOEAs, and TMOEAs can successfully find nondominated solutions preferred by the decision maker.","lang":"eng"}],"publication":"Swarm and Evolutionary Computation","citation":{"mla":"Li, L., et al. “Multiobjective Evolutionary Algorithms Based on Target Region Preferences.” <i>Swarm and Evolutionary Computation</i>, vol. 40, 2018, pp. 196–215, doi:<a href=\"https://doi.org/10.1016/j.swevo.2018.02.006\">10.1016/j.swevo.2018.02.006</a>.","bibtex":"@article{Li_Wang_Trautmann_Jing_Emmerich_2018, title={Multiobjective evolutionary algorithms based on target region preferences}, volume={40}, DOI={<a href=\"https://doi.org/10.1016/j.swevo.2018.02.006\">10.1016/j.swevo.2018.02.006</a>}, journal={Swarm and Evolutionary Computation}, author={Li, L and Wang, Y and Trautmann, Heike and Jing, N and Emmerich, M}, year={2018}, pages={196–215} }","ama":"Li L, Wang Y, Trautmann H, Jing N, Emmerich M. Multiobjective evolutionary algorithms based on target region preferences. <i>Swarm and Evolutionary Computation</i>. 2018;40:196–215. doi:<a href=\"https://doi.org/10.1016/j.swevo.2018.02.006\">10.1016/j.swevo.2018.02.006</a>","ieee":"L. Li, Y. Wang, H. Trautmann, N. Jing, and M. Emmerich, “Multiobjective evolutionary algorithms based on target region preferences,” <i>Swarm and Evolutionary Computation</i>, vol. 40, pp. 196–215, 2018, doi: <a href=\"https://doi.org/10.1016/j.swevo.2018.02.006\">10.1016/j.swevo.2018.02.006</a>.","apa":"Li, L., Wang, Y., Trautmann, H., Jing, N., &#38; Emmerich, M. (2018). Multiobjective evolutionary algorithms based on target region preferences. <i>Swarm and Evolutionary Computation</i>, <i>40</i>, 196–215. <a href=\"https://doi.org/10.1016/j.swevo.2018.02.006\">https://doi.org/10.1016/j.swevo.2018.02.006</a>","short":"L. Li, Y. Wang, H. Trautmann, N. Jing, M. Emmerich, Swarm and Evolutionary Computation 40 (2018) 196–215.","chicago":"Li, L, Y Wang, Heike Trautmann, N Jing, and M Emmerich. “Multiobjective Evolutionary Algorithms Based on Target Region Preferences.” <i>Swarm and Evolutionary Computation</i> 40 (2018): 196–215. <a href=\"https://doi.org/10.1016/j.swevo.2018.02.006\">https://doi.org/10.1016/j.swevo.2018.02.006</a>."},"type":"journal_article","department":[{"_id":"34"},{"_id":"819"}],"date_created":"2023-08-04T07:56:57Z"},{"user_id":"460","_id":"11838","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2018/Eusipco_2018_Schmalenstroeer_Paper.pdf"}],"date_updated":"2023-10-26T08:12:33Z","author":[{"id":"460","last_name":"Schmalenstroeer","first_name":"Joerg","full_name":"Schmalenstroeer, Joerg"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}],"year":"2018","status":"public","title":"Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach","department":[{"_id":"54"}],"oa":"1","type":"conference","date_created":"2019-07-12T05:29:14Z","quality_controlled":"1","abstract":[{"lang":"eng","text":"Distributed sensor data acquisition usually encompasses data sampling by the individual devices, where each of them has its own oscillator driving the local sampling process, resulting in slightly different sampling rates at the individual sensor nodes. Nevertheless, for certain downstream signal processing tasks it is important to compensate even for small sampling rate offsets. Aligning the sampling rates of oscillators which differ only by a few parts-per-million, is, however, challenging and quite different from traditional multirate signal processing tasks. In this paper we propose to transfer a precise but computationally demanding time domain approach, inspired by the Nyquist-Shannon sampling theorem, to an efficient frequency domain implementation. To this end a buffer control is employed which compensates for sampling offsets which are multiples of the sampling period, while a digital filter, realized by the wellknown Overlap-Save method, handles the fractional part of the sampling phase offset. With experiments on artificially misaligned data we investigate the parametrization, the efficiency, and the induced distortions of the proposed resampling method. It is shown that a favorable compromise between residual distortion and computational complexity is achieved, compared to other sampling rate offset compensation techniques."}],"citation":{"bibtex":"@inproceedings{Schmalenstroeer_Haeb-Umbach_2018, title={Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach}, booktitle={26th European Signal Processing Conference (EUSIPCO 2018)}, author={Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2018} }","ama":"Schmalenstroeer J, Haeb-Umbach R. Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach. In: <i>26th European Signal Processing Conference (EUSIPCO 2018)</i>. ; 2018.","mla":"Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach.” <i>26th European Signal Processing Conference (EUSIPCO 2018)</i>, 2018.","chicago":"Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach.” In <i>26th European Signal Processing Conference (EUSIPCO 2018)</i>, 2018.","short":"J. Schmalenstroeer, R. Haeb-Umbach, in: 26th European Signal Processing Conference (EUSIPCO 2018), 2018.","ieee":"J. Schmalenstroeer and R. Haeb-Umbach, “Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach,” 2018.","apa":"Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2018). Efficient Sampling Rate Offset Compensation - An Overlap-Save Based Approach. <i>26th European Signal Processing Conference (EUSIPCO 2018)</i>."},"publication":"26th European Signal Processing Conference (EUSIPCO 2018)"},{"publication":"Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India","citation":{"bibtex":"@inproceedings{Kitza_Michel_Boeddeker_Heitkaemper_Menne_Schlüter_Ney_Schmalenstroeer_Drude_Heymann_et al._2018, title={The RWTH/UPB System Combination for the CHiME 2018 Workshop}, booktitle={Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India}, author={Kitza, Markus and Michel, Wilfried and Boeddeker, Christoph and Heitkaemper, Jens and Menne, Tobias and Schlüter, Ralf and Ney, Hermann and Schmalenstroeer, Joerg and Drude, Lukas and Heymann, Jahn and et al.}, year={2018} }","ama":"Kitza M, Michel W, Boeddeker C, et al. The RWTH/UPB System Combination for the CHiME 2018 Workshop. In: <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>. ; 2018.","mla":"Kitza, Markus, et al. “The RWTH/UPB System Combination for the CHiME 2018 Workshop.” <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>, 2018.","chicago":"Kitza, Markus, Wilfried Michel, Christoph Boeddeker, Jens Heitkaemper, Tobias Menne, Ralf Schlüter, Hermann Ney, et al. “The RWTH/UPB System Combination for the CHiME 2018 Workshop.” In <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>, 2018.","short":"M. Kitza, W. Michel, C. Boeddeker, J. Heitkaemper, T. Menne, R. Schlüter, H. Ney, J. Schmalenstroeer, L. Drude, J. Heymann, R. Haeb-Umbach, in: Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India, 2018.","ieee":"M. Kitza <i>et al.</i>, “The RWTH/UPB System Combination for the CHiME 2018 Workshop,” 2018.","apa":"Kitza, M., Michel, W., Boeddeker, C., Heitkaemper, J., Menne, T., Schlüter, R., Ney, H., Schmalenstroeer, J., Drude, L., Heymann, J., &#38; Haeb-Umbach, R. (2018). The RWTH/UPB System Combination for the CHiME 2018 Workshop. <i>Proc. CHiME 2018 Workshop on Speech Processing in Everyday Environments, Hyderabad, India</i>."},"abstract":[{"text":"This paper describes the systems for the single-array track and the multiple-array track of the 5th CHiME Challenge. The final system is a combination of multiple systems, using Confusion Network Combination (CNC). The different systems presented here are utilizing different front-ends and training sets for a Bidirectional Long Short-Term Memory (BLSTM) Acoustic Model (AM). The front-end was replaced by enhancements provided by Paderborn University [1]. The back-end has been implemented using RASR [2] and RETURNN [3]. Additionally, a system combination including the hypothesis word graphs from the system of the submission [1] has been performed, which results in the final best system.","lang":"eng"}],"quality_controlled":"1","date_created":"2019-07-12T05:29:58Z","type":"conference","oa":"1","department":[{"_id":"54"}],"status":"public","title":"The RWTH/UPB System Combination for the CHiME 2018 Workshop","year":"2018","author":[{"full_name":"Kitza, Markus","last_name":"Kitza","first_name":"Markus"},{"full_name":"Michel, Wilfried","last_name":"Michel","first_name":"Wilfried"},{"id":"40767","full_name":"Boeddeker, Christoph","first_name":"Christoph","last_name":"Boeddeker"},{"first_name":"Jens","last_name":"Heitkaemper","full_name":"Heitkaemper, Jens","id":"27643"},{"full_name":"Menne, Tobias","last_name":"Menne","first_name":"Tobias"},{"full_name":"Schlüter, Ralf","first_name":"Ralf","last_name":"Schlüter"},{"full_name":"Ney, Hermann","last_name":"Ney","first_name":"Hermann"},{"first_name":"Joerg","last_name":"Schmalenstroeer","full_name":"Schmalenstroeer, Joerg","id":"460"},{"id":"11213","full_name":"Drude, Lukas","first_name":"Lukas","last_name":"Drude"},{"id":"9168","full_name":"Heymann, Jahn","first_name":"Jahn","last_name":"Heymann"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}],"date_updated":"2023-10-26T08:12:14Z","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/INTERSPEECH_2018_Heitkaemper_RWTH_Paper.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"11876","user_id":"460"},{"date_created":"2019-07-12T05:29:11Z","type":"conference","department":[{"_id":"54"}],"oa":"1","publication":"ITG 2018, Oldenburg, Germany","citation":{"short":"J. Ebbers, J. Heitkaemper, J. Schmalenstroeer, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.","chicago":"Ebbers, Janek, Jens Heitkaemper, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Benchmarking Neural Network Architectures for Acoustic Sensor Networks.” In <i>ITG 2018, Oldenburg, Germany</i>, 2018.","ieee":"J. Ebbers, J. Heitkaemper, J. Schmalenstroeer, and R. Haeb-Umbach, “Benchmarking Neural Network Architectures for Acoustic Sensor Networks,” 2018.","apa":"Ebbers, J., Heitkaemper, J., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2018). Benchmarking Neural Network Architectures for Acoustic Sensor Networks. <i>ITG 2018, Oldenburg, Germany</i>.","bibtex":"@inproceedings{Ebbers_Heitkaemper_Schmalenstroeer_Haeb-Umbach_2018, title={Benchmarking Neural Network Architectures for Acoustic Sensor Networks}, booktitle={ITG 2018, Oldenburg, Germany}, author={Ebbers, Janek and Heitkaemper, Jens and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2018} }","ama":"Ebbers J, Heitkaemper J, Schmalenstroeer J, Haeb-Umbach R. Benchmarking Neural Network Architectures for Acoustic Sensor Networks. In: <i>ITG 2018, Oldenburg, Germany</i>. ; 2018.","mla":"Ebbers, Janek, et al. “Benchmarking Neural Network Architectures for Acoustic Sensor Networks.” <i>ITG 2018, Oldenburg, Germany</i>, 2018."},"related_material":{"link":[{"description":"Poster","relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Ebbers_Poster.pdf"}]},"quality_controlled":"1","abstract":[{"lang":"eng","text":"Due to their distributed nature wireless acoustic sensor networks offer great potential for improved signal acquisition, processing and classification for applications such as monitoring and surveillance, home automation, or hands-free telecommunication. To reduce the communication demand with a central server and to raise the privacy level it is desirable to perform processing at node level. The limited processing and memory capabilities on a sensor node, however, stand in contrast to the compute and memory intensive deep learning algorithms used in modern speech and audio processing. In this work, we perform benchmarking of commonly used convolutional and recurrent neural network architectures on a Raspberry Pi based acoustic sensor node. We show that it is possible to run medium-sized neural network topologies used for speech enhancement and speech recognition in real time. For acoustic event recognition, where predictions in a lower temporal resolution are sufficient, it is even possible to run current state-of-the-art deep convolutional models with a real-time-factor of 0:11."}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Ebbers_Paper.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"11836","user_id":"460","year":"2018","status":"public","title":"Benchmarking Neural Network Architectures for Acoustic Sensor Networks","author":[{"full_name":"Ebbers, Janek","last_name":"Ebbers","first_name":"Janek","id":"34851"},{"id":"27643","last_name":"Heitkaemper","first_name":"Jens","full_name":"Heitkaemper, Jens"},{"full_name":"Schmalenstroeer, Joerg","first_name":"Joerg","last_name":"Schmalenstroeer","id":"460"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach"}],"date_updated":"2023-10-26T08:12:40Z"},{"citation":{"chicago":"Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming.” In <i>ITG 2018, Oldenburg, Germany</i>, 2018.","short":"J. Schmalenstroeer, R. Haeb-Umbach, in: ITG 2018, Oldenburg, Germany, 2018.","ieee":"J. Schmalenstroeer and R. Haeb-Umbach, “Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming,” 2018.","apa":"Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2018). Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming. <i>ITG 2018, Oldenburg, Germany</i>.","bibtex":"@inproceedings{Schmalenstroeer_Haeb-Umbach_2018, title={Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming}, booktitle={ITG 2018, Oldenburg, Germany}, author={Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2018} }","ama":"Schmalenstroeer J, Haeb-Umbach R. Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming. In: <i>ITG 2018, Oldenburg, Germany</i>. ; 2018.","mla":"Schmalenstroeer, Joerg, and Reinhold Haeb-Umbach. “Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming.” <i>ITG 2018, Oldenburg, Germany</i>, 2018."},"publication":"ITG 2018, Oldenburg, Germany","quality_controlled":"1","abstract":[{"text":"It has been experimentally verified that sampling rate offsets (SROs) between the input channels of an acoustic beamformer have a detrimental effect on the achievable SNR gains. In this paper we derive an analytic model to study the impact of SRO on the estimation of the spatial noise covariance matrix used in MVDR beamforming. It is shown that a perfect compensation of the SRO is impossible if the noise covariance matrix is estimated by time averaging, even if the SRO is perfectly known. The SRO should therefore be compensated for prior to beamformer coefficient estimation. We present a novel scheme where SRO compensation and beamforming closely interact, saving some computational effort compared to separate SRO adjustment followed by acoustic beamforming.","lang":"eng"}],"date_created":"2019-07-12T05:29:15Z","oa":"1","department":[{"_id":"54"}],"type":"conference","author":[{"id":"460","full_name":"Schmalenstroeer, Joerg","last_name":"Schmalenstroeer","first_name":"Joerg"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}],"year":"2018","status":"public","title":"Insights into the Interplay of Sampling Rate Offsets and MVDR Beamforming","date_updated":"2023-10-26T08:12:22Z","language":[{"iso":"eng"}],"_id":"11839","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2018/ITG_2018_Schmalenstroeer_Paper.pdf"}],"user_id":"460"},{"user_id":"85820","publisher":"WTM","_id":"45392","language":[{"iso":"ger"}],"page":"469-472","date_updated":"2023-11-02T08:10:36Z","author":[{"last_name":"Dröse","first_name":"Jennifer","full_name":"Dröse, Jennifer","id":"85820"}],"corporate_editor":["Fachgruppe Didaktik der Mathematik der Universität Paderborn"],"title":"Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts","year":"2018","status":"public","department":[{"_id":"98"}],"type":"conference","date_created":"2023-05-31T08:15:12Z","place":"Münster","extern":"1","citation":{"ama":"Dröse J. Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts. In: Fachgruppe Didaktik der Mathematik der Universität Paderborn, ed. <i>Beiträge zum Mathematikunterricht 2018</i>. WTM; 2018:469-472.","bibtex":"@inproceedings{Dröse_2018, place={Münster}, title={Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts}, booktitle={Beiträge zum Mathematikunterricht 2018}, publisher={WTM}, author={Dröse, Jennifer}, editor={Fachgruppe Didaktik der Mathematik der Universität Paderborn}, year={2018}, pages={469–472} }","mla":"Dröse, Jennifer. “Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts.” <i>Beiträge zum Mathematikunterricht 2018</i>, edited by Fachgruppe Didaktik der Mathematik der Universität Paderborn, WTM, 2018, pp. 469–72.","short":"J. Dröse, in: Fachgruppe Didaktik der Mathematik der Universität Paderborn (Ed.), Beiträge zum Mathematikunterricht 2018, WTM, Münster, 2018, pp. 469–472.","chicago":"Dröse, Jennifer. “Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts.” In <i>Beiträge zum Mathematikunterricht 2018</i>, edited by Fachgruppe Didaktik der Mathematik der Universität Paderborn, 469–72. Münster: WTM, 2018.","apa":"Dröse, J. (2018). Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts. In Fachgruppe Didaktik der Mathematik der Universität Paderborn (Ed.), <i>Beiträge zum Mathematikunterricht 2018</i> (pp. 469–472). WTM.","ieee":"J. Dröse, “Textaufgaben strategisch und sprachlich bewältigen lernen – Pilotstudie zur Wirksamkeit eines Förderkonzepts,” in <i>Beiträge zum Mathematikunterricht 2018</i>, 2018, pp. 469–472."},"publication":"Beiträge zum Mathematikunterricht 2018"}]