[{"date_updated":"2026-09-04T19:41:53Z","publication_status":"published","intvolume":"        39","year":"2022","title":"Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications","publication_identifier":{"issn":["1053-5888","1558-0792"]},"author":[{"first_name":"Emil","last_name":"Bjornson","full_name":"Bjornson, Emil"},{"last_name":"Wymeersch","first_name":"Henk","full_name":"Wymeersch, Henk"},{"first_name":"Bho","orcid":"0000-0002-4582-3938","last_name":"Matthiesen","full_name":"Matthiesen, Bho","id":"126292"},{"last_name":"Popovski","first_name":"Petar","full_name":"Popovski, Petar"},{"full_name":"Sanguinetti, Luca","last_name":"Sanguinetti","first_name":"Luca"},{"full_name":"de Carvalho, Elisabeth","last_name":"de Carvalho","first_name":"Elisabeth"}],"doi":"10.1109/msp.2021.3130549","language":[{"iso":"eng"}],"extern":"1","publication":"IEEE Signal Processing Magazine","issue":"2","type":"journal_article","date_created":"2026-09-04T14:09:03Z","status":"public","user_id":"126292","volume":39,"page":"135-158","_id":"66982","publisher":"Institute of Electrical and Electronics Engineers (IEEE)","citation":{"short":"E. Bjornson, H. Wymeersch, B. Matthiesen, P. Popovski, L. Sanguinetti, E. de Carvalho, IEEE Signal Processing Magazine 39 (2022) 135–158.","chicago":"Bjornson, Emil, Henk Wymeersch, Bho Matthiesen, Petar Popovski, Luca Sanguinetti, and Elisabeth de Carvalho. “Reconfigurable Intelligent Surfaces: A Signal Processing Perspective with Wireless Applications.” <i>IEEE Signal Processing Magazine</i> 39, no. 2 (2022): 135–58. <a href=\"https://doi.org/10.1109/msp.2021.3130549\">https://doi.org/10.1109/msp.2021.3130549</a>.","ieee":"E. Bjornson, H. Wymeersch, B. Matthiesen, P. Popovski, L. Sanguinetti, and E. de Carvalho, “Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications,” <i>IEEE Signal Processing Magazine</i>, vol. 39, no. 2, pp. 135–158, 2022, doi: <a href=\"https://doi.org/10.1109/msp.2021.3130549\">10.1109/msp.2021.3130549</a>.","apa":"Bjornson, E., Wymeersch, H., Matthiesen, B., Popovski, P., Sanguinetti, L., &#38; de Carvalho, E. (2022). Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications. <i>IEEE Signal Processing Magazine</i>, <i>39</i>(2), 135–158. <a href=\"https://doi.org/10.1109/msp.2021.3130549\">https://doi.org/10.1109/msp.2021.3130549</a>","bibtex":"@article{Bjornson_Wymeersch_Matthiesen_Popovski_Sanguinetti_de Carvalho_2022, title={Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications}, volume={39}, DOI={<a href=\"https://doi.org/10.1109/msp.2021.3130549\">10.1109/msp.2021.3130549</a>}, number={2}, journal={IEEE Signal Processing Magazine}, publisher={Institute of Electrical and Electronics Engineers (IEEE)}, author={Bjornson, Emil and Wymeersch, Henk and Matthiesen, Bho and Popovski, Petar and Sanguinetti, Luca and de Carvalho, Elisabeth}, year={2022}, pages={135–158} }","ama":"Bjornson E, Wymeersch H, Matthiesen B, Popovski P, Sanguinetti L, de Carvalho E. Reconfigurable Intelligent Surfaces: A signal processing perspective with wireless applications. <i>IEEE Signal Processing Magazine</i>. 2022;39(2):135-158. doi:<a href=\"https://doi.org/10.1109/msp.2021.3130549\">10.1109/msp.2021.3130549</a>","mla":"Bjornson, Emil, et al. “Reconfigurable Intelligent Surfaces: A Signal Processing Perspective with Wireless Applications.” <i>IEEE Signal Processing Magazine</i>, vol. 39, no. 2, Institute of Electrical and Electronics Engineers (IEEE), 2022, pp. 135–58, doi:<a href=\"https://doi.org/10.1109/msp.2021.3130549\">10.1109/msp.2021.3130549</a>."}},{"oa":"1","citation":{"apa":"Haeb-Umbach, R., Watanabe, S., Nakatani, T., Bacchiani, M., Hoffmeister, B., Seltzer, M. L., Zen, H., &#38; Souden, M. (2019). Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques. <i>IEEE Signal Processing Magazine</i>, <i>36</i>(6), 111–124. <a href=\"https://doi.org/10.1109/MSP.2019.2918706\">https://doi.org/10.1109/MSP.2019.2918706</a>","ieee":"R. Haeb-Umbach <i>et al.</i>, “Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques,” <i>IEEE Signal Processing Magazine</i>, vol. 36, no. 6, pp. 111–124, 2019, doi: <a href=\"https://doi.org/10.1109/MSP.2019.2918706\">10.1109/MSP.2019.2918706</a>.","short":"R. Haeb-Umbach, S. Watanabe, T. Nakatani, M. Bacchiani, B. Hoffmeister, M.L. Seltzer, H. Zen, M. Souden, IEEE Signal Processing Magazine 36 (2019) 111–124.","chicago":"Haeb-Umbach, Reinhold, Shinji Watanabe, Tomohiro Nakatani, Michiel Bacchiani, Bjoern Hoffmeister, Michael L. Seltzer, Heiga Zen, and Mehrez Souden. “Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques.” <i>IEEE Signal Processing Magazine</i> 36, no. 6 (2019): 111–24. <a href=\"https://doi.org/10.1109/MSP.2019.2918706\">https://doi.org/10.1109/MSP.2019.2918706</a>.","mla":"Haeb-Umbach, Reinhold, et al. “Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques.” <i>IEEE Signal Processing Magazine</i>, vol. 36, no. 6, 2019, pp. 111–24, doi:<a href=\"https://doi.org/10.1109/MSP.2019.2918706\">10.1109/MSP.2019.2918706</a>.","ama":"Haeb-Umbach R, Watanabe S, Nakatani T, et al. Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques. <i>IEEE Signal Processing Magazine</i>. 2019;36(6):111-124. doi:<a href=\"https://doi.org/10.1109/MSP.2019.2918706\">10.1109/MSP.2019.2918706</a>","bibtex":"@article{Haeb-Umbach_Watanabe_Nakatani_Bacchiani_Hoffmeister_Seltzer_Zen_Souden_2019, title={Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques}, volume={36}, DOI={<a href=\"https://doi.org/10.1109/MSP.2019.2918706\">10.1109/MSP.2019.2918706</a>}, number={6}, journal={IEEE Signal Processing Magazine}, author={Haeb-Umbach, Reinhold and Watanabe, Shinji and Nakatani, Tomohiro and Bacchiani, Michiel and Hoffmeister, Bjoern and Seltzer, Michael L. and Zen, Heiga and Souden, Mehrez}, year={2019}, pages={111–124} }"},"file_date_updated":"2020-02-06T07:28:26Z","volume":36,"user_id":"242","ddc":["000"],"_id":"15814","page":"111-124","has_accepted_license":"1","status":"public","department":[{"_id":"54"}],"type":"journal_article","date_created":"2020-02-06T07:26:20Z","file":[{"content_type":"application/pdf","file_id":"15815","access_level":"open_access","file_size":1085002,"file_name":"JournalIEEESignal ProcessingMagazine_2019_Haeb-Umbach_Paper.pdf","date_updated":"2020-02-06T07:28:26Z","relation":"main_file","date_created":"2020-02-06T07:28:26Z","creator":"huesera"}],"abstract":[{"text":"Once a popular theme of futuristic science fiction or far-fetched technology forecasts, digital home assistants with a spoken language interface have become a ubiquitous commodity today. This success has been made possible by major advancements in signal processing and machine learning for so-called far-field speech recognition, where the commands are spoken at a distance from the sound capturing device. The challenges encountered are quite unique and different from many other use cases of automatic speech recognition. The purpose of this tutorial article is to describe, in a way amenable to the non-specialist, the key speech processing algorithms that enable reliable fully hands-free speech interaction with digital home assistants. These technologies include multi-channel acoustic echo cancellation, microphone array processing and dereverberation techniques for signal enhancement, reliable wake-up word and end-of-interaction detection, high-quality speech synthesis, as well as sophisticated statistical models for speech and language, learned from large amounts of heterogeneous training data. In all these fields, deep learning has occupied a critical role.","lang":"eng"}],"issue":"6","publication":"IEEE Signal Processing Magazine","doi":"10.1109/MSP.2019.2918706","language":[{"iso":"eng"}],"intvolume":"        36","date_updated":"2023-01-09T11:47:09Z","publication_identifier":{"issn":["1558-0792"]},"author":[{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"},{"full_name":"Watanabe, Shinji","last_name":"Watanabe","first_name":"Shinji"},{"last_name":"Nakatani","first_name":"Tomohiro","full_name":"Nakatani, Tomohiro"},{"full_name":"Bacchiani, Michiel","last_name":"Bacchiani","first_name":"Michiel"},{"full_name":"Hoffmeister, Bjoern","first_name":"Bjoern","last_name":"Hoffmeister"},{"first_name":"Michael L.","last_name":"Seltzer","full_name":"Seltzer, Michael L."},{"full_name":"Zen, Heiga","last_name":"Zen","first_name":"Heiga"},{"last_name":"Souden","first_name":"Mehrez","full_name":"Souden, Mehrez"}],"year":"2019","title":"Speech Processing for Digital Home Assistance: Combining Signal Processing With Deep-Learning Techniques"}]