[{"year":"2016","citation":{"chicago":"Plinge, Axel, Florian Jacob, Reinhold Haeb-Umbach, and Gernot A. Fink. “Acoustic Microphone Geometry Calibration: An Overview and Experimental Evaluation of State-of-the-Art Algorithms.” IEEE Signal Processing Magazine 33, no. 4 (2016): 14–29. https://doi.org/10.1109/MSP.2016.2555198.","apa":"Plinge, A., Jacob, F., Haeb-Umbach, R., & Fink, G. A. (2016). Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms. IEEE Signal Processing Magazine, 33(4), 14–29. https://doi.org/10.1109/MSP.2016.2555198","ama":"Plinge A, Jacob F, Haeb-Umbach R, Fink GA. Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms. IEEE Signal Processing Magazine. 2016;33(4):14-29. doi:10.1109/MSP.2016.2555198","bibtex":"@article{Plinge_Jacob_Haeb-Umbach_Fink_2016, title={Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms}, volume={33}, DOI={10.1109/MSP.2016.2555198}, number={4}, journal={IEEE Signal Processing Magazine}, author={Plinge, Axel and Jacob, Florian and Haeb-Umbach, Reinhold and Fink, Gernot A.}, year={2016}, pages={14–29} }","mla":"Plinge, Axel, et al. “Acoustic Microphone Geometry Calibration: An Overview and Experimental Evaluation of State-of-the-Art Algorithms.” IEEE Signal Processing Magazine, vol. 33, no. 4, 2016, pp. 14–29, doi:10.1109/MSP.2016.2555198.","short":"A. Plinge, F. Jacob, R. Haeb-Umbach, G.A. Fink, IEEE Signal Processing Magazine 33 (2016) 14–29.","ieee":"A. Plinge, F. Jacob, R. Haeb-Umbach, and G. A. Fink, “Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms,” IEEE Signal Processing Magazine, vol. 33, no. 4, pp. 14–29, 2016."},"type":"journal_article","page":"14-29","intvolume":" 33","_id":"11886","issue":"4","author":[{"last_name":"Plinge","full_name":"Plinge, Axel","first_name":"Axel"},{"last_name":"Jacob","full_name":"Jacob, Florian","first_name":"Florian"},{"first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","id":"242"},{"last_name":"Fink","full_name":"Fink, Gernot A.","first_name":"Gernot A."}],"keyword":["Acoustic sensors","Microphones","Portable computers","Smart phones","Wireless communication","Wireless sensor networks"],"publication":"IEEE Signal Processing Magazine","status":"public","date_created":"2019-07-12T05:30:09Z","volume":33,"abstract":[{"text":"Today, we are often surrounded by devices with one or more microphones, such as smartphones, laptops, and wireless microphones. If they are part of an acoustic sensor network, their distribution in the environment can be beneficially exploited for various speech processing tasks. However, applications like speaker localization, speaker tracking, and speech enhancement by beamforming avail themselves of the geometrical configuration of the sensors. Therefore, acoustic microphone geometry calibration has recently become a very active field of research. This article provides an application-oriented, comprehensive survey of existing methods for microphone position self-calibration, which will be categorized by the measurements they use and the scenarios they can calibrate. Selected methods will be evaluated comparatively with real-world recordings.","lang":"eng"}],"user_id":"44006","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:11Z","doi":"10.1109/MSP.2016.2555198","department":[{"_id":"54"}],"publication_identifier":{"issn":["1053-5888"]},"title":"Acoustic Microphone Geometry Calibration: An overview and experimental evaluation of state-of-the-art algorithms"},{"publication_identifier":{"issn":["1948-5719"]},"status":"public","date_created":"2019-05-13T13:18:49Z","quality_controlled":"1","author":[{"last_name":"Bornmann","first_name":"Peter","full_name":"Bornmann, Peter"},{"last_name":"Hemsel","id":"210","first_name":"Tobias","full_name":"Hemsel, Tobias"},{"full_name":"Sextro, Walter","first_name":"Walter","id":"21220","last_name":"Sextro"},{"last_name":"Maeda","first_name":"Takafumi","full_name":"Maeda, Takafumi"},{"full_name":"Morita, Takeshi","first_name":"Takeshi","last_name":"Morita"}],"publication":"Ultrasonics Symposium (IUS), 2012 IEEE International","department":[{"_id":"151"}],"keyword":["cavitation","chemical reactors","microphones","process monitoring","reliability","ultrasonic applications","ultrasonic waves","acoustic properties","cavitation based ultrasound applications","cavitation intensity","change detection reliability","external microphone","malfunction detection reliability","nonperturbing cavitation detection","nonperturbing cavitation monitoring","process monitoring","self-sensing ultrasound transducer","sonochemical reactors","sonochemistry","ultrasound cleaning","ultrasound irradiation","Acoustics","Liquids","Monitoring","Sensors","Sonar equipment","Transducers","Ultrasonic imaging"],"title":"Non-perturbing cavitation detection / monitoring in sonochemical reactors","user_id":"55222","abstract":[{"lang":"eng","text":"To optimize the ultrasound irradiation for cavitation based ultrasound applications like sonochemistry or ultrasound cleaning, the correlation between cavitation intensity and the resulting effect on the process is of interest. Furthermore, changing conditions like temperature and pressure result in varying acoustic properties of the liquid. That might necessitate an adaption of the ultrasound irradiation. To detect such changes during operation, process monitoring is desired. Labor intensive processes, that might be carried out for several hours, also require process monitoring to increase their reliability by detection of changes or malfunctions during operation. In some applications cavitation detection and monitoring can be achieved by the application of sensors in the sound field. Though the application of sensors is possible, this necessitates modifications on the system and the sensor might disturb the sound field. In other applications harsh, process conditions prohibit the application of sensors in the sound field. Therefore alternative techniques for cavitation detection and monitoring are desired. The applicability of an external microphone and a self-sensing ultrasound transducer for cavitation detection were experimentally investigated. Both methods were found to be suitable and easily applicable."}],"type":"conference","year":"2012","citation":{"mla":"Bornmann, Peter, et al. “Non-Perturbing Cavitation Detection / Monitoring in Sonochemical Reactors.” Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–44, doi:10.1109/ULTSYM.2012.0284.","bibtex":"@inproceedings{Bornmann_Hemsel_Sextro_Maeda_Morita_2012, title={Non-perturbing cavitation detection / monitoring in sonochemical reactors}, DOI={10.1109/ULTSYM.2012.0284}, booktitle={Ultrasonics Symposium (IUS), 2012 IEEE International}, author={Bornmann, Peter and Hemsel, Tobias and Sextro, Walter and Maeda, Takafumi and Morita, Takeshi}, year={2012}, pages={1141–1144} }","ama":"Bornmann P, Hemsel T, Sextro W, Maeda T, Morita T. Non-perturbing cavitation detection / monitoring in sonochemical reactors. In: Ultrasonics Symposium (IUS), 2012 IEEE International. ; 2012:1141-1144. doi:10.1109/ULTSYM.2012.0284","apa":"Bornmann, P., Hemsel, T., Sextro, W., Maeda, T., & Morita, T. (2012). Non-perturbing cavitation detection / monitoring in sonochemical reactors. In Ultrasonics Symposium (IUS), 2012 IEEE International (pp. 1141–1144). https://doi.org/10.1109/ULTSYM.2012.0284","chicago":"Bornmann, Peter, Tobias Hemsel, Walter Sextro, Takafumi Maeda, and Takeshi Morita. “Non-Perturbing Cavitation Detection / Monitoring in Sonochemical Reactors.” In Ultrasonics Symposium (IUS), 2012 IEEE International, 1141–44, 2012. https://doi.org/10.1109/ULTSYM.2012.0284.","ieee":"P. Bornmann, T. Hemsel, W. Sextro, T. Maeda, and T. Morita, “Non-perturbing cavitation detection / monitoring in sonochemical reactors,” in Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–1144.","short":"P. Bornmann, T. Hemsel, W. Sextro, T. Maeda, T. Morita, in: Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–1144."},"page":"1141-1144","language":[{"iso":"eng"}],"doi":"10.1109/ULTSYM.2012.0284","_id":"9783","date_updated":"2022-01-06T07:04:20Z"},{"title":"Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition","department":[{"_id":"54"}],"oa":"1","doi":"10.1109/TASL.2007.898454","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"user_id":"44006","abstract":[{"lang":"eng","text":"Maximizing the output signal-to-noise ratio (SNR) of a sensor array in the presence of spatially colored noise leads to a generalized eigenvalue problem. While this approach has extensively been employed in narrowband (antenna) array beamforming, it is typically not used for broadband (microphone) array beamforming due to the uncontrolled amount of speech distortion introduced by a narrowband SNR criterion. In this paper, we show how the distortion of the desired signal can be controlled by a single-channel post-filter, resulting in a performance comparable to the generalized minimum variance distortionless response beamformer, where arbitrary transfer functions relate the source and the microphones. Results are given both for directional and diffuse noise. A novel gradient ascent adaptation algorithm is presented, and its good convergence properties are experimentally revealed by comparison with alternatives from the literature. A key feature of the proposed beamformer is that it operates blindly, i.e., it neither requires knowledge about the array geometry nor an explicit estimation of the transfer functions from source to sensors or the direction-of-arrival."}],"date_created":"2019-07-12T05:30:57Z","status":"public","volume":15,"keyword":["acoustic signal processing","arbitrary transfer function","array signal processing","blind acoustic beamforming","direction-of-arrival","direction-of-arrival estimation","eigenvalues and eigenfunctions","generalized eigenvalue decomposition","gradient ascent adaptation algorithm","microphone arrays","microphones","narrowband array beamforming","sensor array","single-channel post-filter","spatially colored noise","transfer functions"],"publication":"IEEE Transactions on Audio, Speech, and Language Processing","author":[{"last_name":"Warsitz","first_name":"Ernst","full_name":"Warsitz, Ernst"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","id":"242","last_name":"Haeb-Umbach"}],"issue":"5","_id":"11927","intvolume":" 15","page":"1529-1539","type":"journal_article","citation":{"ieee":"E. Warsitz and R. Haeb-Umbach, “Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 15, no. 5, pp. 1529–1539, 2007.","short":"E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 15 (2007) 1529–1539.","mla":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 15, no. 5, 2007, pp. 1529–39, doi:10.1109/TASL.2007.898454.","bibtex":"@article{Warsitz_Haeb-Umbach_2007, title={Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition}, volume={15}, DOI={10.1109/TASL.2007.898454}, number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2007}, pages={1529–1539} }","chicago":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition.” IEEE Transactions on Audio, Speech, and Language Processing 15, no. 5 (2007): 1529–39. https://doi.org/10.1109/TASL.2007.898454.","ama":"Warsitz E, Haeb-Umbach R. Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition. IEEE Transactions on Audio, Speech, and Language Processing. 2007;15(5):1529-1539. doi:10.1109/TASL.2007.898454","apa":"Warsitz, E., & Haeb-Umbach, R. (2007). Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition. IEEE Transactions on Audio, Speech, and Language Processing, 15(5), 1529–1539. https://doi.org/10.1109/TASL.2007.898454"},"year":"2007","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2007/WaHa07.pdf"}]},{"user_id":"44006","title":"Robust speaker direction estimation with particle filtering","abstract":[{"lang":"eng","text":"The paper is concerned with binaural signal processing for a bimodal human-robot interface with hearing and vision. The two microphone signals are processed to obtain an enhanced single-channel input signal for the subsequent speech recognizer and to localize the acoustic source, an important information for establishing a natural human-robot communication. We utilize a robust adaptive algorithm for filter-and-sum beamforming (FSB) and extract speaker direction information from the resulting FIR filter coefficients. Further, particle filtering is applied which conducts a nonlinear Bayesian tracking of speaker movement. Good location accuracy can be achieved even in highly reverberant environments. The results obtained outperform the conventional generalized cross correlation (GCC) method."}],"date_created":"2019-07-12T05:31:01Z","status":"public","department":[{"_id":"54"}],"publication":"IEEE Workshop on Multimedia Signal Processing (MMSP 2004)","keyword":["bimodal human-robot interface","binaural signal processing","enhanced single-channel input signal","filter-and-sum beamforming","filtering theory","FIR filter coefficient","generalized cross correlation method","microphones","microphone signal","nonlinear Bayesian tracking","particle filtering","robust adaptive algorithm","robust speaker direction estimation","signal processing","speech enhancement","speech recognition","speech recognizer","user interfaces"],"author":[{"last_name":"Warsitz","full_name":"Warsitz, Ernst","first_name":"Ernst"},{"last_name":"Haeb-Umbach","id":"242","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold"}],"oa":"1","doi":"10.1109/MMSP.2004.1436569","_id":"11931","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"page":"367-370","citation":{"bibtex":"@inproceedings{Warsitz_Haeb-Umbach_2004, title={Robust speaker direction estimation with particle filtering}, DOI={10.1109/MMSP.2004.1436569}, booktitle={IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2004}, pages={367–370} }","mla":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation with Particle Filtering.” IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–70, doi:10.1109/MMSP.2004.1436569.","apa":"Warsitz, E., & Haeb-Umbach, R. (2004). Robust speaker direction estimation with particle filtering. In IEEE Workshop on Multimedia Signal Processing (MMSP 2004) (pp. 367–370). https://doi.org/10.1109/MMSP.2004.1436569","ama":"Warsitz E, Haeb-Umbach R. Robust speaker direction estimation with particle filtering. In: IEEE Workshop on Multimedia Signal Processing (MMSP 2004). ; 2004:367-370. doi:10.1109/MMSP.2004.1436569","chicago":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation with Particle Filtering.” In IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 367–70, 2004. https://doi.org/10.1109/MMSP.2004.1436569.","ieee":"E. Warsitz and R. Haeb-Umbach, “Robust speaker direction estimation with particle filtering,” in IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–370.","short":"E. Warsitz, R. Haeb-Umbach, in: IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–370."},"year":"2004","type":"conference","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2004/WaHa04.pdf"}]}]