[{"date_created":"2018-04-03T15:08:13Z","place":"New York, NY, USA","department":[{"_id":"27"},{"_id":"518"},{"_id":"78"}],"type":"conference","keyword":["design space exploration","LLVM","partitioning","performance","estimation","funding-intel"],"citation":{"bibtex":"@inproceedings{Kenter_Platzner_Plessl_Kauschke_2011, place={New York, NY, USA}, title={Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures}, DOI={<a href=\"https://doi.org/10.1145/1950413.1950448\">10.1145/1950413.1950448</a>}, booktitle={Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)}, publisher={ACM}, author={Kenter, Tobias and Platzner, Marco and Plessl, Christian and Kauschke, Michael}, year={2011}, pages={177–180} }","short":"T. Kenter, M. Platzner, C. Plessl, M. Kauschke, in: Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA), ACM, New York, NY, USA, 2011, pp. 177–180.","ama":"Kenter T, Platzner M, Plessl C, Kauschke M. Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures. In: <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>. ACM; 2011:177-180. doi:<a href=\"https://doi.org/10.1145/1950413.1950448\">10.1145/1950413.1950448</a>","chicago":"Kenter, Tobias, Marco Platzner, Christian Plessl, and Michael Kauschke. “Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures.” In <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>, 177–80. New York, NY, USA: ACM, 2011. <a href=\"https://doi.org/10.1145/1950413.1950448\">https://doi.org/10.1145/1950413.1950448</a>.","ieee":"T. Kenter, M. Platzner, C. Plessl, and M. Kauschke, “Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures,” in <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>, 2011, pp. 177–180, doi: <a href=\"https://doi.org/10.1145/1950413.1950448\">10.1145/1950413.1950448</a>.","mla":"Kenter, Tobias, et al. “Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures.” <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>, ACM, 2011, pp. 177–80, doi:<a href=\"https://doi.org/10.1145/1950413.1950448\">10.1145/1950413.1950448</a>.","apa":"Kenter, T., Platzner, M., Plessl, C., &#38; Kauschke, M. (2011). Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures. <i>Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)</i>, 177–180. <a href=\"https://doi.org/10.1145/1950413.1950448\">https://doi.org/10.1145/1950413.1950448</a>"},"publication":"Proc. Int. Symp. on Field-Programmable Gate Arrays (FPGA)","quality_controlled":"1","_id":"2200","publisher":"ACM","language":[{"iso":"eng"}],"page":"177-180","user_id":"15278","doi":"10.1145/1950413.1950448","author":[{"id":"3145","first_name":"Tobias","last_name":"Kenter","full_name":"Kenter, Tobias"},{"first_name":"Marco","last_name":"Platzner","full_name":"Platzner, Marco","id":"398"},{"id":"16153","first_name":"Christian","last_name":"Plessl","orcid":"0000-0001-5728-9982","full_name":"Plessl, Christian"},{"full_name":"Kauschke, Michael","first_name":"Michael","last_name":"Kauschke"}],"publication_identifier":{"isbn":["978-1-4503-0554-9"]},"title":"Performance Estimation Framework for Automated Exploration of CPU-Accelerator Architectures","status":"public","year":"2011","date_updated":"2023-09-26T13:45:04Z"},{"date_updated":"2022-01-06T06:51:07Z","year":"2010","status":"public","title":"Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter","author":[{"full_name":"Bevermeier, Maik","last_name":"Bevermeier","first_name":"Maik"},{"first_name":"Oliver","last_name":"Walter","full_name":"Walter, Oliver"},{"full_name":"Peschke, Sven","first_name":"Sven","last_name":"Peschke"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"user_id":"44006","doi":"10.1109/WPNC.2010.5650745","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2010/BeWaPeHa10.pdf"}],"page":"128-134","language":[{"iso":"eng"}],"_id":"11726","abstract":[{"text":"In this paper we present a robust location estimation algorithm especially focused on the accuracy in vertical position. A loosely-coupled error state space Kalman filter, which fuses sensor data of an Inertial Measurement Unit and the output of a Global Positioning System device, is augmented by height information from an altitude measurement unit. This unit consists of a barometric altimeter whose output is fused with topographic map information by a Kalman filter to provide robust information about the current vertical user position. These data replace the less reliable vertical position information provided the GPS device. It is shown that typical barometric errors like thermal divergences and fluctuations in the pressure due to changing weather conditions can be compensated by the topographic map information and the barometric error Kalman filter. The resulting height information is shown not only to be more reliable than height information provided by GPS. It also turns out that it leads to better attitude and thus better overall localization estimation accuracy due to the coupling of spatial orientations via the Direct Cosine Matrix. Results are presented both for artificially generated and field test data, where the user is moving by car.","lang":"eng"}],"publication":"7th Workshop on Positioning Navigation and Communication (WPNC 2010)","citation":{"mla":"Bevermeier, Maik, et al. “Barometric Height Estimation Combined with Map-Matching in a Loosely-Coupled Kalman-Filter.” <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i>, 2010, pp. 128–34, doi:<a href=\"https://doi.org/10.1109/WPNC.2010.5650745\">10.1109/WPNC.2010.5650745</a>.","ama":"Bevermeier M, Walter O, Peschke S, Haeb-Umbach R. Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter. In: <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i>. ; 2010:128-134. doi:<a href=\"https://doi.org/10.1109/WPNC.2010.5650745\">10.1109/WPNC.2010.5650745</a>","bibtex":"@inproceedings{Bevermeier_Walter_Peschke_Haeb-Umbach_2010, title={Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter}, DOI={<a href=\"https://doi.org/10.1109/WPNC.2010.5650745\">10.1109/WPNC.2010.5650745</a>}, booktitle={7th Workshop on Positioning Navigation and Communication (WPNC 2010)}, author={Bevermeier, Maik and Walter, Oliver and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2010}, pages={128–134} }","apa":"Bevermeier, M., Walter, O., Peschke, S., &#38; Haeb-Umbach, R. (2010). Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter. In <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i> (pp. 128–134). <a href=\"https://doi.org/10.1109/WPNC.2010.5650745\">https://doi.org/10.1109/WPNC.2010.5650745</a>","ieee":"M. Bevermeier, O. Walter, S. Peschke, and R. Haeb-Umbach, “Barometric height estimation combined with map-matching in a loosely-coupled Kalman-filter,” in <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i>, 2010, pp. 128–134.","short":"M. Bevermeier, O. Walter, S. Peschke, R. Haeb-Umbach, in: 7th Workshop on Positioning Navigation and Communication (WPNC 2010), 2010, pp. 128–134.","chicago":"Bevermeier, Maik, Oliver Walter, Sven Peschke, and Reinhold Haeb-Umbach. “Barometric Height Estimation Combined with Map-Matching in a Loosely-Coupled Kalman-Filter.” In <i>7th Workshop on Positioning Navigation and Communication (WPNC 2010)</i>, 128–34, 2010. <a href=\"https://doi.org/10.1109/WPNC.2010.5650745\">https://doi.org/10.1109/WPNC.2010.5650745</a>."},"type":"conference","keyword":["altitude measurement unit","barometers","barometric altimeter","barometric error Kalman filter","barometric height estimation","direct cosine matrix","global positioning system","Global Positioning System","GPS device","height information","height measurement","inertial measurement unit","Kalman filters","loosely-coupled error state space Kalman filter","loosely-coupled Kalman-filter","map matching","robust information","robust location estimation","sensor fusion","topographic map information","vertical user position"],"department":[{"_id":"54"}],"oa":"1","date_created":"2019-07-12T05:27:04Z"},{"date_created":"2019-07-12T05:29:23Z","department":[{"_id":"54"}],"keyword":["ASR","AURORA5 database","automatic speech recognition","Bayesian inference","belief networks","CMLLR","computational complexity","constrained maximum likelihood linear regression","least mean squares methods","LMPSC computation","logarithmic Mel power spectrum","maximum likelihood estimation","Mel frequency cepstral coefficients","MFCC feature vectors","microphone signal","minimum mean square error estimation","model-based feature enhancement","regression analysis","reverberant speech recognition","reverberation","RIR energy","room impulse response","speech recognition","stochastic observation model","stochastic processes"],"type":"journal_article","issue":"7","publication":"IEEE Transactions on Audio, Speech, and Language Processing","abstract":[{"text":"In this paper, we present a new technique for automatic speech recognition (ASR) in reverberant environments. Our approach is aimed at the enhancement of the logarithmic Mel power spectrum, which is computed at an intermediate stage to obtain the widely used Mel frequency cepstral coefficients (MFCCs). Given the reverberant logarithmic Mel power spectral coefficients (LMPSCs), a minimum mean square error estimate of the clean LMPSCs is computed by carrying out Bayesian inference. We employ switching linear dynamical models as an a priori model for the dynamics of the clean LMPSCs. Further, we derive a stochastic observation model which relates the clean to the reverberant LMPSCs through a simplified model of the room impulse response (RIR). This model requires only two parameters, namely RIR energy and reverberation time, which can be estimated from the captured microphone signal. The performance of the proposed enhancement technique is studied on the AURORA5 database and compared to that of constrained maximum-likelihood linear regression (CMLLR). It is shown by experimental results that our approach significantly outperforms CMLLR and that up to 80\\% of the errors caused by the reverberation are recovered. In addition to the fact that the approach is compatible with the standard MFCC feature vectors, it leaves the ASR back-end unchanged. It is of moderate computational complexity and suitable for real time applications.","lang":"eng"}],"language":[{"iso":"eng"}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2010/KrHa10.pdf","open_access":"1"}],"doi":"10.1109/TASL.2010.2049684","author":[{"full_name":"Krueger, Alexander","first_name":"Alexander","last_name":"Krueger"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"title":"Model-Based Feature Enhancement for Reverberant Speech Recognition","year":"2010","intvolume":"        18","date_updated":"2022-01-06T06:51:11Z","oa":"1","citation":{"ieee":"A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant Speech Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 18, no. 7, pp. 1692–1707, 2010.","apa":"Krueger, A., &#38; Haeb-Umbach, R. (2010). Model-Based Feature Enhancement for Reverberant Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>18</i>(7), 1692–1707. <a href=\"https://doi.org/10.1109/TASL.2010.2049684\">https://doi.org/10.1109/TASL.2010.2049684</a>","chicago":"Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement for Reverberant Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 18, no. 7 (2010): 1692–1707. <a href=\"https://doi.org/10.1109/TASL.2010.2049684\">https://doi.org/10.1109/TASL.2010.2049684</a>.","short":"A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 18 (2010) 1692–1707.","mla":"Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement for Reverberant Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 18, no. 7, 2010, pp. 1692–707, doi:<a href=\"https://doi.org/10.1109/TASL.2010.2049684\">10.1109/TASL.2010.2049684</a>.","bibtex":"@article{Krueger_Haeb-Umbach_2010, title={Model-Based Feature Enhancement for Reverberant Speech Recognition}, volume={18}, DOI={<a href=\"https://doi.org/10.1109/TASL.2010.2049684\">10.1109/TASL.2010.2049684</a>}, number={7}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2010}, pages={1692–1707} }","ama":"Krueger A, Haeb-Umbach R. Model-Based Feature Enhancement for Reverberant Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2010;18(7):1692-1707. doi:<a href=\"https://doi.org/10.1109/TASL.2010.2049684\">10.1109/TASL.2010.2049684</a>"},"_id":"11846","page":"1692-1707","volume":18,"user_id":"44006","status":"public"},{"keyword":["covariance matrices","expectation-maximisation algorithm","expectation-maximization algorithm","global positioning system","Global Positioning System","GPS","inertial measurement unit","interacting multiple model approach","Kalman filters","multilevel sensor fusion","narrow street canyons","narrow tunnels","online parameter estimation","parameter estimation","road vehicles","robust vehicle localization","sensor fusion","state noise covariances","time-variant multilevel Kalman filter","vehicle tracking algorithm"],"type":"conference","oa":"1","department":[{"_id":"54"}],"date_created":"2019-07-12T05:27:01Z","abstract":[{"text":"In this paper we present a novel vehicle tracking algorithm, which is based on multi-level sensor fusion of GPS (global positioning system) with Inertial Measurement Unit sensor data. It is shown that the robustness of the system to temporary dropouts of the GPS signal, which may occur due to limited visibility of satellites in narrow street canyons or tunnels, is greatly improved by sensor fusion. We further demonstrate how the observation and state noise covariances of the employed Kalman filters can be estimated alongside the filtering by an application of the Expectation-Maximization algorithm. The proposed time-variant multi-level Kalman filter is shown to outperform an Interacting Multiple Model approach while at the same time being computationally less demanding.","lang":"eng"}],"publication":"6th Workshop on Positioning Navigation and Communication (WPNC 2009)","citation":{"mla":"Bevermeier, Maik, et al. “Robust Vehicle Localization Based on Multi-Level Sensor Fusion and Online Parameter Estimation.” <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i>, 2009, pp. 235–42, doi:<a href=\"https://doi.org/10.1109/WPNC.2009.4907833\">10.1109/WPNC.2009.4907833</a>.","ama":"Bevermeier M, Peschke S, Haeb-Umbach R. Robust vehicle localization based on multi-level sensor fusion and online parameter estimation. In: <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i>. ; 2009:235-242. doi:<a href=\"https://doi.org/10.1109/WPNC.2009.4907833\">10.1109/WPNC.2009.4907833</a>","bibtex":"@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Robust vehicle localization based on multi-level sensor fusion and online parameter estimation}, DOI={<a href=\"https://doi.org/10.1109/WPNC.2009.4907833\">10.1109/WPNC.2009.4907833</a>}, booktitle={6th Workshop on Positioning Navigation and Communication (WPNC 2009)}, author={Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009}, pages={235–242} }","apa":"Bevermeier, M., Peschke, S., &#38; Haeb-Umbach, R. (2009). Robust vehicle localization based on multi-level sensor fusion and online parameter estimation. In <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i> (pp. 235–242). <a href=\"https://doi.org/10.1109/WPNC.2009.4907833\">https://doi.org/10.1109/WPNC.2009.4907833</a>","ieee":"M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Robust vehicle localization based on multi-level sensor fusion and online parameter estimation,” in <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i>, 2009, pp. 235–242.","short":"M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp. 235–242.","chicago":"Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Robust Vehicle Localization Based on Multi-Level Sensor Fusion and Online Parameter Estimation.” In <i>6th Workshop on Positioning Navigation and Communication (WPNC 2009)</i>, 235–42, 2009. <a href=\"https://doi.org/10.1109/WPNC.2009.4907833\">https://doi.org/10.1109/WPNC.2009.4907833</a>."},"doi":"10.1109/WPNC.2009.4907833","user_id":"44006","page":"235-242","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09.pdf","open_access":"1"}],"language":[{"iso":"eng"}],"_id":"11723","date_updated":"2022-01-06T06:51:07Z","year":"2009","title":"Robust vehicle localization based on multi-level sensor fusion and online parameter estimation","status":"public","author":[{"first_name":"Maik","last_name":"Bevermeier","full_name":"Bevermeier, Maik"},{"full_name":"Peschke, Sven","first_name":"Sven","last_name":"Peschke"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}]},{"user_id":"44006","doi":"10.1109/VETECS.2009.5073634","language":[{"iso":"eng"}],"_id":"11724","page":"1-5","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09-1.pdf"}],"date_updated":"2022-01-06T06:51:07Z","author":[{"last_name":"Bevermeier","first_name":"Maik","full_name":"Bevermeier, Maik"},{"last_name":"Peschke","first_name":"Sven","full_name":"Peschke, Sven"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"year":"2009","title":"Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning","status":"public","department":[{"_id":"54"}],"oa":"1","type":"conference","keyword":["computational complexity","expectation-maximisation algorithm","Global Positioning System","inertial measurement unit","inertial navigation","interacting multiple model","iterative block expectation-maximization algorithm","Kalman filters","multi-stage Kalman filter","parameter estimation","road vehicles","vehicle positioning","vehicle tracking"],"date_created":"2019-07-12T05:27:02Z","abstract":[{"lang":"eng","text":"In this paper we present a novel vehicle tracking method which is based on multi-stage Kalman filtering of GPS and IMU sensor data. After individual Kalman filtering of GPS and IMU measurements the estimates of the orientation of the vehicle are combined in an optimal manner to improve the robustness towards drift errors. The tracking algorithm incorporates the estimation of time-variant covariance parameters by using an iterative block Expectation-Maximization algorithm to account for time-variant driving conditions and measurement quality. The proposed system is compared to an interacting multiple model approach (IMM) and achieves improved localization accuracy at lower computational complexity. Furthermore we show how the joint parameter estimation and localizaiton can be conducted with streaming input data to be able to track vehicles in a real driving environment."}],"citation":{"bibtex":"@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning}, DOI={<a href=\"https://doi.org/10.1109/VETECS.2009.5073634\">10.1109/VETECS.2009.5073634</a>}, booktitle={IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)}, author={Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009}, pages={1–5} }","ama":"Bevermeier M, Peschke S, Haeb-Umbach R. Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning. In: <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i>. ; 2009:1-5. doi:<a href=\"https://doi.org/10.1109/VETECS.2009.5073634\">10.1109/VETECS.2009.5073634</a>","mla":"Bevermeier, Maik, et al. “Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.” <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 2009, pp. 1–5, doi:<a href=\"https://doi.org/10.1109/VETECS.2009.5073634\">10.1109/VETECS.2009.5073634</a>.","short":"M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5.","chicago":"Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.” In <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 1–5, 2009. <a href=\"https://doi.org/10.1109/VETECS.2009.5073634\">https://doi.org/10.1109/VETECS.2009.5073634</a>.","ieee":"M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning,” in <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i>, 2009, pp. 1–5.","apa":"Bevermeier, M., Peschke, S., &#38; Haeb-Umbach, R. (2009). Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning. In <i>IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)</i> (pp. 1–5). <a href=\"https://doi.org/10.1109/VETECS.2009.5073634\">https://doi.org/10.1109/VETECS.2009.5073634</a>"},"publication":"IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)"},{"citation":{"apa":"Windmann, S., &#38; Haeb-Umbach, R. (2009). Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>17</i>(8), 1577–1590. <a href=\"https://doi.org/10.1109/TASL.2009.2023172\">https://doi.org/10.1109/TASL.2009.2023172</a>","ieee":"S. Windmann and R. Haeb-Umbach, “Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 17, no. 8, pp. 1577–1590, 2009.","chicago":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 17, no. 8 (2009): 1577–90. <a href=\"https://doi.org/10.1109/TASL.2009.2023172\">https://doi.org/10.1109/TASL.2009.2023172</a>.","short":"S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 17 (2009) 1577–1590.","mla":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 17, no. 8, 2009, pp. 1577–90, doi:<a href=\"https://doi.org/10.1109/TASL.2009.2023172\">10.1109/TASL.2009.2023172</a>.","ama":"Windmann S, Haeb-Umbach R. Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2009;17(8):1577-1590. doi:<a href=\"https://doi.org/10.1109/TASL.2009.2023172\">10.1109/TASL.2009.2023172</a>","bibtex":"@article{Windmann_Haeb-Umbach_2009, title={Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition}, volume={17}, DOI={<a href=\"https://doi.org/10.1109/TASL.2009.2023172\">10.1109/TASL.2009.2023172</a>}, number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={1577–1590} }"},"oa":"1","status":"public","_id":"11938","page":"1577-1590","volume":17,"user_id":"44006","issue":"8","publication":"IEEE Transactions on Audio, Speech, and Language Processing","abstract":[{"text":"In this paper, parameter estimation of a state-space model of noise or noisy speech cepstra is investigated. A blockwise EM algorithm is derived for the estimation of the state and observation noise covariance from noise-only input data. It is supposed to be used during the offline training mode of a speech recognizer. Further a sequential online EM algorithm is developed to adapt the observation noise covariance on noisy speech cepstra at its input. The estimated parameters are then used in model-based speech feature enhancement for noise-robust automatic speech recognition. Experiments on the AURORA4 database lead to improved recognition results with a linear state model compared to the assumption of stationary noise.","lang":"eng"}],"date_created":"2019-07-12T05:31:09Z","department":[{"_id":"54"}],"keyword":["AURORA4 database","blockwise EM algorithm","covariance analysis","linear state model","noise covariance","noise-robust automatic speech recognition","noisy speech cepstra","offline training mode","parameter estimation","speech recognition","speech recognition equipment","speech recognizer","state-space methods","state-space model"],"type":"journal_article","author":[{"full_name":"Windmann, Stefan","last_name":"Windmann","first_name":"Stefan"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"title":"Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition","year":"2009","intvolume":"        17","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-2.pdf","open_access":"1"}],"doi":"10.1109/TASL.2009.2023172"},{"abstract":[{"text":"The generalized sidelobe canceller by Griffith and Jim is a robust beamforming method to enhance a desired (speech) signal in the presence of stationary noise. Its performance depends to a high degree on the construction of the blocking matrix which produces noise reference signals for the subsequent adaptive interference canceller. Especially in reverberated environments the beamformer may suffer from signal leakage and reduced noise suppression. In this paper a new blocking matrix is proposed. It is based on a generalized eigenvalue problem whose solution provides an indirect estimation of the transfer functions from the source to the sensors. The quality of the new generalized eigenvector blocking matrix is studied in simulated rooms with different reverberation times and is compared to alternatives proposed in the literature.","lang":"eng"}],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)","citation":{"chicago":"Warsitz, Ernst, Alexander Krueger, and Reinhold Haeb-Umbach. “Speech Enhancement with a New Generalized Eigenvector Blocking Matrix for Application in a Generalized Sidelobe Canceller.” In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 73–76, 2008. <a href=\"https://doi.org/10.1109/ICASSP.2008.4517549\">https://doi.org/10.1109/ICASSP.2008.4517549</a>.","short":"E. Warsitz, A. Krueger, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 73–76.","apa":"Warsitz, E., Krueger, A., &#38; Haeb-Umbach, R. (2008). Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller. In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i> (pp. 73–76). <a href=\"https://doi.org/10.1109/ICASSP.2008.4517549\">https://doi.org/10.1109/ICASSP.2008.4517549</a>","ieee":"E. Warsitz, A. Krueger, and R. Haeb-Umbach, “Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 2008, pp. 73–76.","ama":"Warsitz E, Krueger A, Haeb-Umbach R. Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller. In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>. ; 2008:73-76. doi:<a href=\"https://doi.org/10.1109/ICASSP.2008.4517549\">10.1109/ICASSP.2008.4517549</a>","bibtex":"@inproceedings{Warsitz_Krueger_Haeb-Umbach_2008, title={Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2008.4517549\">10.1109/ICASSP.2008.4517549</a>}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)}, author={Warsitz, Ernst and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2008}, pages={73–76} }","mla":"Warsitz, Ernst, et al. “Speech Enhancement with a New Generalized Eigenvector Blocking Matrix for Application in a Generalized Sidelobe Canceller.” <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 2008, pp. 73–76, doi:<a href=\"https://doi.org/10.1109/ICASSP.2008.4517549\">10.1109/ICASSP.2008.4517549</a>."},"type":"conference","keyword":["adaptive interference canceller","adaptive signal processing","array signal processing","beamforming method","eigenvalues and eigenfunctions","generalized eigenvector blocking matrix","generalized sidelobe canceller","interference suppression","matrix algebra","noise suppression","speech enhancement","transfer function estimation","transfer functions"],"oa":"1","department":[{"_id":"54"}],"date_created":"2019-07-12T05:31:06Z","date_updated":"2022-01-06T06:51:12Z","year":"2008","title":"Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller","status":"public","author":[{"first_name":"Ernst","last_name":"Warsitz","full_name":"Warsitz, Ernst"},{"last_name":"Krueger","first_name":"Alexander","full_name":"Krueger, Alexander"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"doi":"10.1109/ICASSP.2008.4517549","user_id":"44006","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2008/WaKrHa08.pdf","open_access":"1"}],"page":"73-76","_id":"11935","language":[{"iso":"eng"}]},{"citation":{"ieee":"R. Haeb-Umbach and M. Bevermeier, “OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>, 2007, vol. 3, pp. III-277-III–280.","apa":"Haeb-Umbach, R., &#38; Bevermeier, M. (2007). OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain. In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i> (Vol. 3, pp. III-277-III–280). <a href=\"https://doi.org/10.1109/ICASSP.2007.366526\">https://doi.org/10.1109/ICASSP.2007.366526</a>","chicago":"Haeb-Umbach, Reinhold, and Maik Bevermeier. “OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain.” In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>, 3:III-277-III–280, 2007. <a href=\"https://doi.org/10.1109/ICASSP.2007.366526\">https://doi.org/10.1109/ICASSP.2007.366526</a>.","short":"R. Haeb-Umbach, M. Bevermeier, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007), 2007, pp. III-277-III–280.","mla":"Haeb-Umbach, Reinhold, and Maik Bevermeier. “OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain.” <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>, vol. 3, 2007, pp. III-277-III–280, doi:<a href=\"https://doi.org/10.1109/ICASSP.2007.366526\">10.1109/ICASSP.2007.366526</a>.","bibtex":"@inproceedings{Haeb-Umbach_Bevermeier_2007, title={OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain}, volume={3}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2007.366526\">10.1109/ICASSP.2007.366526</a>}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)}, author={Haeb-Umbach, Reinhold and Bevermeier, Maik}, year={2007}, pages={III-277-III–280} }","ama":"Haeb-Umbach R, Bevermeier M. OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain. In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)</i>. Vol 3. ; 2007:III-277-III-280. doi:<a href=\"https://doi.org/10.1109/ICASSP.2007.366526\">10.1109/ICASSP.2007.366526</a>"},"oa":"1","status":"public","user_id":"44006","volume":3,"page":"III-277-III-280","_id":"11785","abstract":[{"lang":"eng","text":"In this paper we present a novel channel impulse response estimation technique for block-oriented OFDM transmission based on combining estimators: the estimates provided by a Kalman filter operating in the time domain and a Wiener filter in the frequency domain are optimally combined by taking into account their estimated error covariances. The resulting estimator turns out to be identical to the MAP estimator of correlated jointly Gaussian mean vectors. Different variants of the proposed scheme are experimentally investigated in an EEEE 802.11a-like system setup. They compare favourably with known approaches from the literature resulting in reduced mean square estimation error and bit error rate. Further, robustness and complexity issues are discussed"}],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2007)","keyword":["bit error rate","block-oriented OFDM transmission","channel estimation","channel impulse response estimation","combining estimators","error statistics","frequency domain estimation","Gaussian mean vectors","Gaussian processes","Kalman filter","Kalman filters","MAP estimator","maximum likelihood estimation","OFDM channel estimation","OFDM modulation","time domain estimation","time-frequency analysis","Wiener filter","Wiener filters"],"type":"conference","department":[{"_id":"54"}],"date_created":"2019-07-12T05:28:13Z","date_updated":"2022-01-06T06:51:08Z","intvolume":"         3","year":"2007","title":"OFDM Channel Estimation Based on Combined Estimation in Time and Frequency Domain","author":[{"id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach"},{"full_name":"Bevermeier, Maik","first_name":"Maik","last_name":"Bevermeier"}],"doi":"10.1109/ICASSP.2007.366526","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2007/HaBe07.pdf","open_access":"1"}],"language":[{"iso":"eng"}]},{"date_created":"2019-07-12T05:30:06Z","type":"conference","keyword":["additive noise","cellular radio","channel estimation","cochannel interference","COST 207 channel models","downlink transmission bursts","fading channels","fading process","GSM downlink signalling","mobile terminals","multipath channels","multipath propagation","power density spectrum","statistical analysis","statistical properties","telecommunication links","telecommunication terminals","velocity estimation"],"department":[{"_id":"54"}],"oa":"1","publication":"4th Workshop on Positioning Navigation and Communication (WPNC 2007)","citation":{"mla":"Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling.” <i>4th Workshop on Positioning Navigation and Communication (WPNC 2007)</i>, 2007, pp. 217–22, doi:<a href=\"https://doi.org/10.1109/WPNC.2007.353637\">10.1109/WPNC.2007.353637</a>.","ama":"Peschke S, Haeb-Umbach R. Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling. In: <i>4th Workshop on Positioning Navigation and Communication (WPNC 2007)</i>. ; 2007:217-222. doi:<a href=\"https://doi.org/10.1109/WPNC.2007.353637\">10.1109/WPNC.2007.353637</a>","bibtex":"@inproceedings{Peschke_Haeb-Umbach_2007, title={Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling}, DOI={<a href=\"https://doi.org/10.1109/WPNC.2007.353637\">10.1109/WPNC.2007.353637</a>}, booktitle={4th Workshop on Positioning Navigation and Communication (WPNC 2007)}, author={Peschke, Sven and Haeb-Umbach, Reinhold}, year={2007}, pages={217–222} }","apa":"Peschke, S., &#38; Haeb-Umbach, R. (2007). Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling. In <i>4th Workshop on Positioning Navigation and Communication (WPNC 2007)</i> (pp. 217–222). <a href=\"https://doi.org/10.1109/WPNC.2007.353637\">https://doi.org/10.1109/WPNC.2007.353637</a>","ieee":"S. Peschke and R. Haeb-Umbach, “Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling,” in <i>4th Workshop on Positioning Navigation and Communication (WPNC 2007)</i>, 2007, pp. 217–222.","short":"S. Peschke, R. Haeb-Umbach, in: 4th Workshop on Positioning Navigation and Communication (WPNC 2007), 2007, pp. 217–222.","chicago":"Peschke, Sven, and Reinhold Haeb-Umbach. “Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling.” In <i>4th Workshop on Positioning Navigation and Communication (WPNC 2007)</i>, 217–22, 2007. <a href=\"https://doi.org/10.1109/WPNC.2007.353637\">https://doi.org/10.1109/WPNC.2007.353637</a>."},"abstract":[{"lang":"eng","text":"In this paper, we experimentally evaluate algorithms for velocity estimation of a GSM 900 mobile terminal which are based on the analysis of the statistical properties of the fast fading process. It is shown how theses statistics can be obtained from the training sequences present in downlink transmission bursts without establishing an active connection. Realistic simulations of a GSM channel according to the COST 207 channel models have been conducted. These models incorporate effects like multipath propagation, fading, cochannel interference and additive noise. It is shown that velocity estimation by searching for the maximum slope of the power density spectrum of the fast fading performs best."}],"page":"217-222","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2007/PeHa07.pdf","open_access":"1"}],"_id":"11883","language":[{"iso":"eng"}],"user_id":"44006","doi":"10.1109/WPNC.2007.353637","title":"Velocity Estimation of Mobile Terminals by Exploiting GSM Downlink Signalling","status":"public","year":"2007","author":[{"last_name":"Peschke","first_name":"Sven","full_name":"Peschke, Sven"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"date_updated":"2022-01-06T06:51:11Z"},{"publication":"IEEE Transactions on Audio, Speech, and Language Processing","issue":"5","abstract":[{"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.","lang":"eng"}],"date_created":"2019-07-12T05:30:57Z","department":[{"_id":"54"}],"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"],"type":"journal_article","author":[{"first_name":"Ernst","last_name":"Warsitz","full_name":"Warsitz, Ernst"},{"last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"year":"2007","title":"Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition","intvolume":"        15","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2007/WaHa07.pdf"}],"doi":"10.1109/TASL.2007.898454","citation":{"short":"E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 15 (2007) 1529–1539.","chicago":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 15, no. 5 (2007): 1529–39. <a href=\"https://doi.org/10.1109/TASL.2007.898454\">https://doi.org/10.1109/TASL.2007.898454</a>.","apa":"Warsitz, E., &#38; Haeb-Umbach, R. (2007). Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>15</i>(5), 1529–1539. <a href=\"https://doi.org/10.1109/TASL.2007.898454\">https://doi.org/10.1109/TASL.2007.898454</a>","ieee":"E. Warsitz and R. Haeb-Umbach, “Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 15, no. 5, pp. 1529–1539, 2007.","ama":"Warsitz E, Haeb-Umbach R. Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2007;15(5):1529-1539. doi:<a href=\"https://doi.org/10.1109/TASL.2007.898454\">10.1109/TASL.2007.898454</a>","bibtex":"@article{Warsitz_Haeb-Umbach_2007, title={Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition}, volume={15}, DOI={<a href=\"https://doi.org/10.1109/TASL.2007.898454\">10.1109/TASL.2007.898454</a>}, number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2007}, pages={1529–1539} }","mla":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Blind Acoustic Beamforming Based on Generalized Eigenvalue Decomposition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 15, no. 5, 2007, pp. 1529–39, doi:<a href=\"https://doi.org/10.1109/TASL.2007.898454\">10.1109/TASL.2007.898454</a>."},"oa":"1","status":"public","_id":"11927","page":"1529-1539","volume":15,"user_id":"44006"},{"oa":"1","citation":{"mla":"Ion, Valentin, and Reinhold Haeb-Umbach. “An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features.” <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, vol. 1, 2006, p. I, doi:<a href=\"https://doi.org/10.1109/ICASSP.2006.1659984\">10.1109/ICASSP.2006.1659984</a>.","ama":"Ion V, Haeb-Umbach R. An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features. In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>. Vol 1. ; 2006:I. doi:<a href=\"https://doi.org/10.1109/ICASSP.2006.1659984\">10.1109/ICASSP.2006.1659984</a>","bibtex":"@inproceedings{Ion_Haeb-Umbach_2006, title={An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features}, volume={1}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2006.1659984\">10.1109/ICASSP.2006.1659984</a>}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}, author={Ion, Valentin and Haeb-Umbach, Reinhold}, year={2006}, pages={I} }","apa":"Ion, V., &#38; Haeb-Umbach, R. (2006). An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features. In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i> (Vol. 1, p. I). <a href=\"https://doi.org/10.1109/ICASSP.2006.1659984\">https://doi.org/10.1109/ICASSP.2006.1659984</a>","ieee":"V. Ion and R. Haeb-Umbach, “An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, 2006, vol. 1, p. I.","chicago":"Ion, Valentin, and Reinhold Haeb-Umbach. “An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features.” In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, 1:I, 2006. <a href=\"https://doi.org/10.1109/ICASSP.2006.1659984\">https://doi.org/10.1109/ICASSP.2006.1659984</a>.","short":"V. Ion, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 2006, p. I."},"page":"I","_id":"11824","user_id":"44006","volume":1,"status":"public","date_created":"2019-07-12T05:28:58Z","keyword":["distributed speech recognition","least mean squares methods","MAP estimate","maximum likelihood estimation","MMSE estimate","packet loss compensation scheme","packet switched communication","posteriori probability density function","robust error mitigation method","soft-features","speech recognition","table lookup","voice communication","wireless channels"],"type":"conference","department":[{"_id":"54"}],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)","abstract":[{"text":"Soft-feature based speech recognition, which is an example of uncertainty decoding, has been proven to be a robust error mitigation method for distributed speech recognition over wireless channels exhibiting bit errors. In this paper we extend this concept to packet-oriented transmissions. The a posteriori probability density function of the lost feature vector, given the closest received neighbours, is computed. In the experiments, the nearest frame repetition, which is shown to be equivalent to the MAP estimate, outperforms the MMSE estimate for long bursts. Taking the variance into account at the speech recognition stage results in superior performance compared to classical schemes using point estimates. A computationally and memory efficient implementation of the proposed packet loss compensation scheme based on table lookup is presented","lang":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2006/IoHa06-2.pdf"}],"language":[{"iso":"eng"}],"doi":"10.1109/ICASSP.2006.1659984","title":"An Inexpensive Packet Loss Compensation Scheme for Distributed Speech Recognition Based on Soft-Features","year":"2006","author":[{"full_name":"Ion, Valentin","last_name":"Ion","first_name":"Valentin"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"date_updated":"2022-01-06T06:51:10Z","intvolume":"         1"},{"user_id":"44006","volume":4,"page":"iv/797-iv/800 Vol. 4","_id":"11930","status":"public","oa":"1","citation":{"short":"E. Warsitz, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005), 2005, p. iv/797-iv/800 Vol. 4.","chicago":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming by Adaptive Principal Component Analysis.” In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, 4:iv/797-iv/800 Vol. 4, 2005. <a href=\"https://doi.org/10.1109/ICASSP.2005.1416129\">https://doi.org/10.1109/ICASSP.2005.1416129</a>.","apa":"Warsitz, E., &#38; Haeb-Umbach, R. (2005). Acoustic filter-and-sum beamforming by adaptive principal component analysis. In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)</i> (Vol. 4, p. iv/797-iv/800 Vol. 4). <a href=\"https://doi.org/10.1109/ICASSP.2005.1416129\">https://doi.org/10.1109/ICASSP.2005.1416129</a>","ieee":"E. Warsitz and R. Haeb-Umbach, “Acoustic filter-and-sum beamforming by adaptive principal component analysis,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, 2005, vol. 4, p. iv/797-iv/800 Vol. 4.","ama":"Warsitz E, Haeb-Umbach R. Acoustic filter-and-sum beamforming by adaptive principal component analysis. In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)</i>. Vol 4. ; 2005:iv/797-iv/800 Vol. 4. doi:<a href=\"https://doi.org/10.1109/ICASSP.2005.1416129\">10.1109/ICASSP.2005.1416129</a>","bibtex":"@inproceedings{Warsitz_Haeb-Umbach_2005, title={Acoustic filter-and-sum beamforming by adaptive principal component analysis}, volume={4}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2005.1416129\">10.1109/ICASSP.2005.1416129</a>}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2005}, pages={iv/797-iv/800 Vol. 4} }","mla":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Acoustic Filter-and-Sum Beamforming by Adaptive Principal Component Analysis.” <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)</i>, vol. 4, 2005, p. iv/797-iv/800 Vol. 4, doi:<a href=\"https://doi.org/10.1109/ICASSP.2005.1416129\">10.1109/ICASSP.2005.1416129</a>."},"doi":"10.1109/ICASSP.2005.1416129","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2005/WaHa05.pdf"}],"language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:12Z","intvolume":"         4","title":"Acoustic filter-and-sum beamforming by adaptive principal component analysis","year":"2005","author":[{"last_name":"Warsitz","first_name":"Ernst","full_name":"Warsitz, Ernst"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach"}],"keyword":["acoustic filter-and-sum beamforming","acoustic room impulses","acoustic signal processing","adaptive principal component analysis","adaptive signal processing","architectural acoustics","constrained optimization problem","cross power spectral density","deterministic algorithm","deterministic algorithms","distant-talking environments","eigenvalues and eigenfunctions","eigenvector","enhanced signal","filter-and-sum beamformer","FIR filter coefficients","FIR filter coefficients","FIR filters","gradient methods","human-machine interfaces","iterative estimation","iterative methods","largest eigenvalue","microphone signals","multichannel signal processing","optimisation","principal component analysis","spectral analysis","stochastic gradient ascent algorithm","stochastic processes"],"type":"conference","department":[{"_id":"54"}],"date_created":"2019-07-12T05:31:00Z","abstract":[{"text":"For human-machine interfaces in distant-talking environments multichannel signal processing is often employed to obtain an enhanced signal for subsequent processing. In this paper we propose a novel adaptation algorithm for a filter-and-sum beamformer to adjust the coefficients of FIR filters to changing acoustic room impulses, e.g. due to speaker movement. A deterministic and a stochastic gradient ascent algorithm are derived from a constrained optimization problem, which iteratively estimates the eigenvector corresponding to the largest eigenvalue of the cross power spectral density of the microphone signals. The method does not require an explicit estimation of the speaker location. The experimental results show fast adaptation and excellent robustness of the proposed algorithm.","lang":"eng"}],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2005)"},{"user_id":"44006","doi":"10.1109/MMSP.2004.1436569","page":"367-370","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2004/WaHa04.pdf"}],"_id":"11931","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:12Z","year":"2004","title":"Robust speaker direction estimation with particle filtering","status":"public","author":[{"last_name":"Warsitz","first_name":"Ernst","full_name":"Warsitz, Ernst"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"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"],"type":"conference","department":[{"_id":"54"}],"oa":"1","date_created":"2019-07-12T05:31:01Z","abstract":[{"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.","lang":"eng"}],"publication":"IEEE Workshop on Multimedia Signal Processing (MMSP 2004)","citation":{"mla":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation with Particle Filtering.” <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>, 2004, pp. 367–70, doi:<a href=\"https://doi.org/10.1109/MMSP.2004.1436569\">10.1109/MMSP.2004.1436569</a>.","ama":"Warsitz E, Haeb-Umbach R. Robust speaker direction estimation with particle filtering. In: <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>. ; 2004:367-370. doi:<a href=\"https://doi.org/10.1109/MMSP.2004.1436569\">10.1109/MMSP.2004.1436569</a>","bibtex":"@inproceedings{Warsitz_Haeb-Umbach_2004, title={Robust speaker direction estimation with particle filtering}, DOI={<a href=\"https://doi.org/10.1109/MMSP.2004.1436569\">10.1109/MMSP.2004.1436569</a>}, booktitle={IEEE Workshop on Multimedia Signal Processing (MMSP 2004)}, author={Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2004}, pages={367–370} }","apa":"Warsitz, E., &#38; Haeb-Umbach, R. (2004). Robust speaker direction estimation with particle filtering. In <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i> (pp. 367–370). <a href=\"https://doi.org/10.1109/MMSP.2004.1436569\">https://doi.org/10.1109/MMSP.2004.1436569</a>","ieee":"E. Warsitz and R. Haeb-Umbach, “Robust speaker direction estimation with particle filtering,” in <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>, 2004, pp. 367–370.","short":"E. Warsitz, R. Haeb-Umbach, in: IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–370.","chicago":"Warsitz, Ernst, and Reinhold Haeb-Umbach. “Robust Speaker Direction Estimation with Particle Filtering.” In <i>IEEE Workshop on Multimedia Signal Processing (MMSP 2004)</i>, 367–70, 2004. <a href=\"https://doi.org/10.1109/MMSP.2004.1436569\">https://doi.org/10.1109/MMSP.2004.1436569</a>."}},{"language":[{"iso":"eng"}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2001/Ha01.pdf","open_access":"1"}],"doi":"10.1109/89.906003","author":[{"id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold"}],"title":"Automatic generation of phonetic regression class trees for MLLR adaptation","year":"2001","intvolume":"         9","date_updated":"2022-01-06T06:51:08Z","date_created":"2019-07-12T05:28:04Z","department":[{"_id":"54"}],"keyword":["acoustic space","adaptation experiments","automatic generation","bottom-up clustering","broad phonetic class regression trees","correlation criterion","correlation methods","maximum likelihood estimation","maximum likelihood linear regression based speaker adaptation","MLLR adaptation","pattern clustering","phonetic regression class trees","speaker-independent training data","speech recognition","speech units","statistical analysis","trees (mathematics)"],"type":"journal_article","publication":"IEEE Transactions on Speech and Audio Processing","issue":"3","abstract":[{"lang":"eng","text":"In this paper, it is shown that a correlation criterion is the appropriate criterion for bottom-up clustering to obtain broad phonetic class regression trees for maximum likelihood linear regression (MLLR)-based speaker adaptation. The correlation structure among speech units is estimated on the speaker-independent training data. In adaptation experiments the tree outperformed a regression tree obtained from clustering according to closeness in acoustic space and achieved results comparable with those of a manually designed broad phonetic class tree"}],"_id":"11778","page":"299-302","volume":9,"user_id":"44006","status":"public","oa":"1","citation":{"mla":"Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class Trees for MLLR Adaptation.” <i>IEEE Transactions on Speech and Audio Processing</i>, vol. 9, no. 3, 2001, pp. 299–302, doi:<a href=\"https://doi.org/10.1109/89.906003\">10.1109/89.906003</a>.","ama":"Haeb-Umbach R. Automatic generation of phonetic regression class trees for MLLR adaptation. <i>IEEE Transactions on Speech and Audio Processing</i>. 2001;9(3):299-302. doi:<a href=\"https://doi.org/10.1109/89.906003\">10.1109/89.906003</a>","bibtex":"@article{Haeb-Umbach_2001, title={Automatic generation of phonetic regression class trees for MLLR adaptation}, volume={9}, DOI={<a href=\"https://doi.org/10.1109/89.906003\">10.1109/89.906003</a>}, number={3}, journal={IEEE Transactions on Speech and Audio Processing}, author={Haeb-Umbach, Reinhold}, year={2001}, pages={299–302} }","apa":"Haeb-Umbach, R. (2001). Automatic generation of phonetic regression class trees for MLLR adaptation. <i>IEEE Transactions on Speech and Audio Processing</i>, <i>9</i>(3), 299–302. <a href=\"https://doi.org/10.1109/89.906003\">https://doi.org/10.1109/89.906003</a>","ieee":"R. Haeb-Umbach, “Automatic generation of phonetic regression class trees for MLLR adaptation,” <i>IEEE Transactions on Speech and Audio Processing</i>, vol. 9, no. 3, pp. 299–302, 2001.","short":"R. Haeb-Umbach, IEEE Transactions on Speech and Audio Processing 9 (2001) 299–302.","chicago":"Haeb-Umbach, Reinhold. “Automatic Generation of Phonetic Regression Class Trees for MLLR Adaptation.” <i>IEEE Transactions on Speech and Audio Processing</i> 9, no. 3 (2001): 299–302. <a href=\"https://doi.org/10.1109/89.906003\">https://doi.org/10.1109/89.906003</a>."}}]