[{"user_id":"44006","department":[{"_id":"54"}],"_id":"11740","language":[{"iso":"eng"}],"keyword":["Gaussian noise","maximum likelihood estimation","parameter estimation","GMM parameter","Gaussian mixture model","MAP estimation","Map-based estimation","maximum a-posteriori estimation","maximum likelihood technique","noisy observation","sequential estimation framework","white Gaussian noise","Additive noise","Gaussian mixture model","Maximum likelihood estimation","Noise measurement","Gaussian mixture model","Maximum a posteriori estimation","Maximum likelihood estimation"],"type":"conference","publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)","status":"public","abstract":[{"lang":"eng","text":"In this contribution we derive the Maximum A-Posteriori (MAP) estimates of the parameters of a Gaussian Mixture Model (GMM) in the presence of noisy observations. We assume the distortion to be white Gaussian noise of known mean and variance. An approximate conjugate prior of the GMM parameters is derived allowing for a computationally efficient implementation in a sequential estimation framework. Simulations on artificially generated data demonstrate the superiority of the proposed method compared to the Maximum Likelihood technique and to the ordinary MAP approach, whose estimates are corrected by the known statistics of the distortion in a straightforward manner."}],"date_created":"2019-07-12T05:27:20Z","author":[{"full_name":"Chinaev, Aleksej","last_name":"Chinaev","first_name":"Aleksej"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"oa":"1","date_updated":"2022-01-06T06:51:08Z","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13.pdf","open_access":"1"}],"doi":"10.1109/ICASSP.2013.6638279","title":"MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations","related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13_Poster.pdf","description":"Poster","relation":"supplementary_material"}]},"publication_identifier":{"issn":["1520-6149"]},"citation":{"apa":"Chinaev, A., & Haeb-Umbach, R. (2013). MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations. In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) (pp. 3352–3356). https://doi.org/10.1109/ICASSP.2013.6638279","short":"A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.","bibtex":"@inproceedings{Chinaev_Haeb-Umbach_2013, title={MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations}, DOI={10.1109/ICASSP.2013.6638279}, booktitle={38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2013}, pages={3352–3356} }","mla":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.” 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–56, doi:10.1109/ICASSP.2013.6638279.","ieee":"A. Chinaev and R. Haeb-Umbach, “MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.","chicago":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.” In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 3352–56, 2013. https://doi.org/10.1109/ICASSP.2013.6638279.","ama":"Chinaev A, Haeb-Umbach R. MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations. In: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:3352-3356. doi:10.1109/ICASSP.2013.6638279"},"page":"3352-3356","year":"2013"},{"keyword":["Bayes methods","compensation","error statistics","reverberation","speech recognition","Bayesian feature enhancement","background noise","clean speech feature vectors","compensation","connected digits recognition task","error statistics","memory requirements","noisy reverberant data","posteriori probability density function","recursive formulation","reverberant logarithmic mel power spectral coefficients","robust automatic speech recognition","signal-to-noise ratios","time-variant observation","word error rate reduction","Robust automatic speech recognition","model-based Bayesian feature enhancement","observation model for reverberant and noisy speech","recursive observation model"],"language":[{"iso":"eng"}],"_id":"11862","department":[{"_id":"54"}],"user_id":"44006","abstract":[{"text":"In this contribution we extend a previously proposed Bayesian approach for the enhancement of reverberant logarithmic mel power spectral coefficients for robust automatic speech recognition to the additional compensation of background noise. A recently proposed observation model is employed whose time-variant observation error statistics are obtained as a side product of the inference of the a posteriori probability density function of the clean speech feature vectors. Further a reduction of the computational effort and the memory requirements are achieved by using a recursive formulation of the observation model. The performance of the proposed algorithms is first experimentally studied on a connected digits recognition task with artificially created noisy reverberant data. It is shown that the use of the time-variant observation error model leads to a significant error rate reduction at low signal-to-noise ratios compared to a time-invariant model. Further experiments were conducted on a 5000 word task recorded in a reverberant and noisy environment. A significant word error rate reduction was obtained demonstrating the effectiveness of the approach on real-world data.","lang":"eng"}],"status":"public","publication":"IEEE Transactions on Audio, Speech, and Language Processing","type":"journal_article","title":"Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition","doi":"10.1109/TASL.2013.2258013","date_updated":"2022-01-06T06:51:11Z","volume":21,"date_created":"2019-07-12T05:29:42Z","author":[{"first_name":"Volker","full_name":"Leutnant, Volker","last_name":"Leutnant"},{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"year":"2013","intvolume":" 21","page":"1640-1652","citation":{"short":"V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 21 (2013) 1640–1652.","bibtex":"@article{Leutnant_Krueger_Haeb-Umbach_2013, title={Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition}, volume={21}, DOI={10.1109/TASL.2013.2258013}, number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2013}, pages={1640–1652} }","mla":"Leutnant, Volker, et al. “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, no. 8, 2013, pp. 1640–52, doi:10.1109/TASL.2013.2258013.","apa":"Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2013). Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 21(8), 1640–1652. https://doi.org/10.1109/TASL.2013.2258013","chicago":"Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” IEEE Transactions on Audio, Speech, and Language Processing 21, no. 8 (2013): 1640–52. https://doi.org/10.1109/TASL.2013.2258013.","ieee":"V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 21, no. 8, pp. 1640–1652, 2013.","ama":"Leutnant V, Krueger A, Haeb-Umbach R. Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing. 2013;21(8):1640-1652. doi:10.1109/TASL.2013.2258013"},"issue":"8"},{"status":"public","abstract":[{"text":"In this paper we present a speech presence probability (SPP) estimation algorithmwhich exploits both temporal and spectral correlations of speech. To this end, the SPP estimation is formulated as the posterior probability estimation of the states of a two-dimensional (2D) Hidden Markov Model (HMM). We derive an iterative algorithm to decode the 2D-HMM which is based on the turbo principle. The experimental results show that indeed the SPP estimates improve from iteration to iteration, and further clearly outperform another state-of-the-art SPP estimation algorithm.","lang":"eng"}],"publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)","type":"conference","language":[{"iso":"eng"}],"keyword":["correlation methods","estimation theory","hidden Markov models","iterative methods","probability","spectral analysis","speech processing","2D HMM","SPP estimates","iterative algorithm","posterior probability estimation","spectral correlation","speech presence probability estimation","state-of-the-art SPP estimation algorithm","temporal correlation","turbo principle","two-dimensional hidden Markov model","Correlation","Decoding","Estimation","Iterative decoding","Noise","Speech","Vectors"],"department":[{"_id":"54"}],"user_id":"44006","_id":"11917","page":"863-867","citation":{"ama":"Vu DHT, Haeb-Umbach R. Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation. In: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013). ; 2013:863-867. doi:10.1109/ICASSP.2013.6637771","ieee":"D. H. T. Vu and R. Haeb-Umbach, “Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation,” in 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.","chicago":"Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle for Exploiting Temporal and Spectral Correlations in Speech Presence Probability Estimation.” In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 863–67, 2013. https://doi.org/10.1109/ICASSP.2013.6637771.","short":"D.H.T. Vu, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.","bibtex":"@inproceedings{Vu_Haeb-Umbach_2013, title={Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation}, DOI={10.1109/ICASSP.2013.6637771}, booktitle={38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)}, author={Vu, Dang Hai Tran and Haeb-Umbach, Reinhold}, year={2013}, pages={863–867} }","mla":"Vu, Dang Hai Tran, and Reinhold Haeb-Umbach. “Using the Turbo Principle for Exploiting Temporal and Spectral Correlations in Speech Presence Probability Estimation.” 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–67, doi:10.1109/ICASSP.2013.6637771.","apa":"Vu, D. H. T., & Haeb-Umbach, R. (2013). Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation. In 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) (pp. 863–867). https://doi.org/10.1109/ICASSP.2013.6637771"},"year":"2013","publication_identifier":{"issn":["1520-6149"]},"doi":"10.1109/ICASSP.2013.6637771","title":"Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation","date_created":"2019-07-12T05:30:45Z","author":[{"first_name":"Dang Hai Tran","full_name":"Vu, Dang Hai Tran","last_name":"Vu"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold"}],"date_updated":"2022-01-06T06:51:12Z"},{"_id":"11818","user_id":"460","department":[{"_id":"54"}],"keyword":["SQL","navigation","smart phones","wireless LAN","RSSI","SQL database","complete multilevel office building","inertial sensor information","inertial smartphone sensors","map renderer","received signal strength index information","relative position estimates","server based indoor navigation","step detection","wireless-LAN access points","Smartphone","fingerprint","indoor navigation","map tile"],"language":[{"iso":"eng"}],"type":"conference","publication":"Positioning Navigation and Communication (WPNC), 2013 10th Workshop on","abstract":[{"lang":"eng","text":"In this paper we present a system for indoor navigation based on received signal strength index information of Wireless-LAN access points and relative position estimates. The relative position information is gathered from inertial smartphone sensors using a step detection and an orientation estimate. Our map data is hosted on a server employing a map renderer and a SQL database. The database includes a complete multilevel office building, within which the user can navigate. During navigation, the client retrieves the position estimate from the server, together with the corresponding map tiles to visualize the user's position on the smartphone display."}],"status":"public","date_updated":"2023-10-26T08:09:36Z","oa":"1","date_created":"2019-07-12T05:28:51Z","author":[{"first_name":"Manh Kha","last_name":"Hoang","full_name":"Hoang, Manh Kha"},{"full_name":"Schmitz, Sarah","last_name":"Schmitz","first_name":"Sarah"},{"first_name":"Christian","last_name":"Drueke","full_name":"Drueke, Christian"},{"last_name":"Vu","full_name":"Vu, Dang Hai Tran","first_name":"Dang Hai Tran"},{"id":"460","full_name":"Schmalenstroeer, Joerg","last_name":"Schmalenstroeer","first_name":"Joerg"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold"}],"title":"Server based indoor navigation using RSSI and inertial sensor information","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrScHa2013.pdf"}],"doi":"10.1109/WPNC.2013.6533263","quality_controlled":"1","related_material":{"link":[{"relation":"supplementary_material","description":"Poster","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HoScDrTrScHa2013_Poster.pdf"}]},"year":"2013","citation":{"ama":"Hoang MK, Schmitz S, Drueke C, Vu DHT, Schmalenstroeer J, Haeb-Umbach R. Server based indoor navigation using RSSI and inertial sensor information. In: Positioning Navigation and Communication (WPNC), 2013 10th Workshop On. ; 2013:1-6. doi:10.1109/WPNC.2013.6533263","chicago":"Hoang, Manh Kha, Sarah Schmitz, Christian Drueke, Dang Hai Tran Vu, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. “Server Based Indoor Navigation Using RSSI and Inertial Sensor Information.” In Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 1–6, 2013. https://doi.org/10.1109/WPNC.2013.6533263.","ieee":"M. K. Hoang, S. Schmitz, C. Drueke, D. H. T. Vu, J. Schmalenstroeer, and R. Haeb-Umbach, “Server based indoor navigation using RSSI and inertial sensor information,” in Positioning Navigation and Communication (WPNC), 2013 10th Workshop on, 2013, pp. 1–6, doi: 10.1109/WPNC.2013.6533263.","apa":"Hoang, M. K., Schmitz, S., Drueke, C., Vu, D. H. T., Schmalenstroeer, J., & Haeb-Umbach, R. (2013). Server based indoor navigation using RSSI and inertial sensor information. Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 1–6. https://doi.org/10.1109/WPNC.2013.6533263","bibtex":"@inproceedings{Hoang_Schmitz_Drueke_Vu_Schmalenstroeer_Haeb-Umbach_2013, title={Server based indoor navigation using RSSI and inertial sensor information}, DOI={10.1109/WPNC.2013.6533263}, booktitle={Positioning Navigation and Communication (WPNC), 2013 10th Workshop on}, author={Hoang, Manh Kha and Schmitz, Sarah and Drueke, Christian and Vu, Dang Hai Tran and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2013}, pages={1–6} }","short":"M.K. Hoang, S. Schmitz, C. Drueke, D.H.T. Vu, J. Schmalenstroeer, R. Haeb-Umbach, in: Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 2013, pp. 1–6.","mla":"Hoang, Manh Kha, et al. “Server Based Indoor Navigation Using RSSI and Inertial Sensor Information.” Positioning Navigation and Communication (WPNC), 2013 10th Workshop On, 2013, pp. 1–6, doi:10.1109/WPNC.2013.6533263."},"page":"1-6"},{"abstract":[{"text":"For the valuation of fast growing innovative firms Schwartz and Moon (Financ Anal J 56:62–75, 2000), (Financ Rev 36:7–26, 2001) develop a fundamental valuation model where key parameters follow stochastic processes. While prior research shows promising potential for this model, it has never been tested on a large scale dataset. Thus, guided by economic theory, this paper is the first to design a large-scale applicable implementation on around 30,000 technology firm quarter observations from 1992 to 2009 for the US to assess this model. Evaluating the feasibility and performance of the Schwartz-Moon model reveals that it is comparably accurate to the traditional sales multiple with key advantages in valuing small and non-listed firms. Most importantly, however, the model is able to indicate severe market over- or undervaluation from a fundamental perspective. We demonstrate that a trading strategy based on our implementation has significant investment value. Consequently, the model seems suitable for detecting misvaluations as the dot-com bubble.","lang":"eng"}],"publication":"Journal of Business Economics (VHB-JOURQUAL 4 Ranking B)","language":[{"iso":"eng"}],"keyword":["Schwartz-Moon model","Market mispricing","Empirical test","Company valuation","Trading strategy"],"year":"2013","issue":"9","quality_controlled":"1","title":"Valuing high technology growth firms","date_created":"2018-10-31T11:31:56Z","publisher":"Springer","status":"public","type":"journal_article","extern":"1","article_type":"original","department":[{"_id":"275"}],"user_id":"115848","_id":"5192","intvolume":" 83","page":"947-984","citation":{"bibtex":"@article{Klobucnik_Sievers_2013, title={Valuing high technology growth firms}, volume={83}, DOI={https://doi.org/10.1007/s11573-013-0684-2}, number={9}, journal={Journal of Business Economics (VHB-JOURQUAL 4 Ranking B)}, publisher={Springer}, author={Klobucnik, Jan and Sievers, Sönke}, year={2013}, pages={947–984} }","short":"J. Klobucnik, S. Sievers, Journal of Business Economics (VHB-JOURQUAL 4 Ranking B) 83 (2013) 947–984.","mla":"Klobucnik, Jan, and Sönke Sievers. “Valuing High Technology Growth Firms.” Journal of Business Economics (VHB-JOURQUAL 4 Ranking B), vol. 83, no. 9, Springer, 2013, pp. 947–84, doi:https://doi.org/10.1007/s11573-013-0684-2.","apa":"Klobucnik, J., & Sievers, S. (2013). Valuing high technology growth firms. Journal of Business Economics (VHB-JOURQUAL 4 Ranking B), 83(9), 947–984. https://doi.org/10.1007/s11573-013-0684-2","ama":"Klobucnik J, Sievers S. Valuing high technology growth firms. Journal of Business Economics (VHB-JOURQUAL 4 Ranking B). 2013;83(9):947-984. doi:https://doi.org/10.1007/s11573-013-0684-2","ieee":"J. Klobucnik and S. Sievers, “Valuing high technology growth firms,” Journal of Business Economics (VHB-JOURQUAL 4 Ranking B), vol. 83, no. 9, pp. 947–984, 2013, doi: https://doi.org/10.1007/s11573-013-0684-2.","chicago":"Klobucnik, Jan, and Sönke Sievers. “Valuing High Technology Growth Firms.” Journal of Business Economics (VHB-JOURQUAL 4 Ranking B) 83, no. 9 (2013): 947–84. https://doi.org/10.1007/s11573-013-0684-2."},"jel":["G11","G12","G17","G33"],"publication_status":"published","doi":"https://doi.org/10.1007/s11573-013-0684-2","main_file_link":[{"url":"https://link.springer.com/article/10.1007/s11573-013-0684-2"}],"volume":83,"author":[{"full_name":"Klobucnik, Jan","last_name":"Klobucnik","first_name":"Jan"},{"first_name":"Sönke","last_name":"Sievers","full_name":"Sievers, Sönke","id":"46447"}],"date_updated":"2026-04-09T08:00:16Z"},{"title":"Extended dividend, cash flow, and residual income valuation models: Accounting for deviations from ideal conditions","date_created":"2018-10-31T07:58:17Z","publisher":"Wiley Online Library","year":"2013","issue":"1","quality_controlled":"1","language":[{"iso":"eng"}],"keyword":["Dividend Discount Model","Residual Income","Discounted Cash Flow","Dirty Surplus","Terminal Value","Valuation Error"],"abstract":[{"text":"Standard equity valuation approaches (i.e., DDM, RIM, and DCF model) are derived under the assumption of ideal conditions, such as infinite payoffs and clean surplus accounting. Because these conditions are hardly ever met, we extend the standard approaches, based on the fundamental principle of financial statement articulation. The extended models are then tested empirically by employing two sets of forecasts: (1) analyst forecasts provided by Value Line and (2) forecasts generated by cross-sectional regression models. The main result is that our extended models yield considerably smaller valuation errors. Moreover, by construction, identical value estimates are obtained across the extended models. By reestablishing empirical equivalence under non-ideal conditions, our approach provides a benchmark that enables us to quantify the errors resulting from individual deviations from ideal conditions, and thus, to analyze the robustness of the standard approaches. Finally, by providing a level playing field for the different valuation approaches, our findings have implications for other empirical settings, for example, estimating the implied cost of capital. ","lang":"eng"}],"publication":"Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+)","main_file_link":[{"url":"http://onlinelibrary.wiley.com/doi/10.1111/j.1911-3846.2011.01148.x/abstract"}],"doi":"10.2139/ssrn.1145201","author":[{"first_name":"Nicolas","last_name":"Heinrichs","full_name":"Heinrichs, Nicolas"},{"last_name":"Hess","full_name":"Hess, Dieter","first_name":"Dieter"},{"first_name":"Carsten","full_name":"Homburg, Carsten","last_name":"Homburg"},{"first_name":"Michael","last_name":"Lorenz","full_name":"Lorenz, Michael"},{"first_name":"Sönke","full_name":"Sievers, Sönke","id":"46447","last_name":"Sievers"}],"volume":30,"date_updated":"2026-04-09T08:22:32Z","jel":["G12","G14","M41"],"citation":{"ama":"Heinrichs N, Hess D, Homburg C, Lorenz M, Sievers S. Extended dividend, cash flow, and residual income valuation models: Accounting for deviations from ideal conditions. Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+). 2013;30(1):42-79. doi:10.2139/ssrn.1145201","ieee":"N. Heinrichs, D. Hess, C. Homburg, M. Lorenz, and S. Sievers, “Extended dividend, cash flow, and residual income valuation models: Accounting for deviations from ideal conditions,” Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+), vol. 30, no. 1, pp. 42–79, 2013, doi: 10.2139/ssrn.1145201.","chicago":"Heinrichs, Nicolas, Dieter Hess, Carsten Homburg, Michael Lorenz, and Sönke Sievers. “Extended Dividend, Cash Flow, and Residual Income Valuation Models: Accounting for Deviations from Ideal Conditions.” Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+) 30, no. 1 (2013): 42–79. https://doi.org/10.2139/ssrn.1145201.","bibtex":"@article{Heinrichs_Hess_Homburg_Lorenz_Sievers_2013, title={Extended dividend, cash flow, and residual income valuation models: Accounting for deviations from ideal conditions}, volume={30}, DOI={10.2139/ssrn.1145201}, number={1}, journal={Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+)}, publisher={Wiley Online Library}, author={Heinrichs, Nicolas and Hess, Dieter and Homburg, Carsten and Lorenz, Michael and Sievers, Sönke}, year={2013}, pages={42–79} }","mla":"Heinrichs, Nicolas, et al. “Extended Dividend, Cash Flow, and Residual Income Valuation Models: Accounting for Deviations from Ideal Conditions.” Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+), vol. 30, no. 1, Wiley Online Library, 2013, pp. 42–79, doi:10.2139/ssrn.1145201.","short":"N. Heinrichs, D. Hess, C. Homburg, M. Lorenz, S. Sievers, Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+) 30 (2013) 42–79.","apa":"Heinrichs, N., Hess, D., Homburg, C., Lorenz, M., & Sievers, S. (2013). Extended dividend, cash flow, and residual income valuation models: Accounting for deviations from ideal conditions. Contemporary Accounting Research (VHB-JOURQUAL 4 Ranking A+), 30(1), 42–79. https://doi.org/10.2139/ssrn.1145201"},"page":"42-79","intvolume":" 30","related_material":{"link":[{"url":"http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1145201","relation":"earlier_version"}]},"publication_status":"published","extern":"1","article_type":"original","user_id":"115848","department":[{"_id":"275"}],"_id":"5113","status":"public","type":"journal_article"},{"page":"117-122","citation":{"short":"M. Becker, M. Luckey, S. Becker, in: {Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}, ACM, New York, NY, USA, 2012, pp. 117–122.","bibtex":"@inproceedings{Becker_Luckey_Becker_2012, place={New York, NY, USA}, title={Model-driven Performance Engineering of Self-adaptive Systems: A Survey}, DOI={10.1145/2304696.2304716}, booktitle={{Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}}, publisher={ACM}, author={Becker, Matthias and Luckey, Markus and Becker, Steffen}, year={2012}, pages={117–122} }","mla":"Becker, Matthias, et al. “Model-Driven Performance Engineering of Self-Adaptive Systems: A Survey.” {Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}, ACM, 2012, pp. 117–22, doi:10.1145/2304696.2304716.","apa":"Becker, M., Luckey, M., & Becker, S. (2012). Model-driven Performance Engineering of Self-adaptive Systems: A Survey. In {Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)} (pp. 117–122). New York, NY, USA: ACM. https://doi.org/10.1145/2304696.2304716","ieee":"M. Becker, M. Luckey, and S. Becker, “Model-driven Performance Engineering of Self-adaptive Systems: A Survey,” in {Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}, 2012, pp. 117–122.","chicago":"Becker, Matthias, Markus Luckey, and Steffen Becker. “Model-Driven Performance Engineering of Self-Adaptive Systems: A Survey.” In {Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}, 117–22. New York, NY, USA: ACM, 2012. https://doi.org/10.1145/2304696.2304716.","ama":"Becker M, Luckey M, Becker S. Model-driven Performance Engineering of Self-adaptive Systems: A Survey. In: {Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}. New York, NY, USA: ACM; 2012:117-122. doi:10.1145/2304696.2304716"},"place":"New York, NY, USA","year":"2012","publication_identifier":{"isbn":["978-1-4503-1346-9"]},"doi":"10.1145/2304696.2304716","title":"Model-driven Performance Engineering of Self-adaptive Systems: A Survey","author":[{"first_name":"Matthias","full_name":"Becker, Matthias","last_name":"Becker"},{"full_name":"Luckey, Markus","last_name":"Luckey","first_name":"Markus"},{"first_name":"Steffen","last_name":"Becker","full_name":"Becker, Steffen"}],"date_created":"2021-07-15T08:38:08Z","publisher":"ACM","date_updated":"2022-01-06T06:55:39Z","status":"public","publication":"{Proceedings of the 8th International ACM SIGSOFT Conference on Quality of Software Architectures (QoSA)}","type":"conference","keyword":["model-driven performance engineering","self-*","Self-adaptation","software performance"],"user_id":"4870","_id":"22737"},{"publication":"Ultrasonics Symposium (IUS), 2012 IEEE International","type":"conference","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."}],"status":"public","_id":"9783","department":[{"_id":"151"}],"user_id":"55222","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"],"language":[{"iso":"eng"}],"publication_identifier":{"issn":["1948-5719"]},"quality_controlled":"1","year":"2012","page":"1141-1144","citation":{"short":"P. Bornmann, T. Hemsel, W. Sextro, T. Maeda, T. Morita, in: Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 1141–1144.","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} }","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.","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","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.","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.","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"},"date_updated":"2022-01-06T07:04:20Z","author":[{"first_name":"Peter","last_name":"Bornmann","full_name":"Bornmann, Peter"},{"full_name":"Hemsel, Tobias","id":"210","last_name":"Hemsel","first_name":"Tobias"},{"first_name":"Walter","last_name":"Sextro","id":"21220","full_name":"Sextro, Walter"},{"full_name":"Maeda, Takafumi","last_name":"Maeda","first_name":"Takafumi"},{"last_name":"Morita","full_name":"Morita, Takeshi","first_name":"Takeshi"}],"date_created":"2019-05-13T13:18:49Z","title":"Non-perturbing cavitation detection / monitoring in sonochemical reactors","doi":"10.1109/ULTSYM.2012.0284"},{"quality_controlled":"1","publication_identifier":{"issn":["1948-5719"]},"year":"2012","citation":{"short":"M. Hunstig, T. Hemsel, W. Sextro, in: Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 277–280.","mla":"Hunstig, Matthias, et al. “An Efficient Simulation Technique for High-Frequency Piezoelectric Inertia Motors.” Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 277–80, doi:10.1109/ULTSYM.2012.0068.","bibtex":"@inproceedings{Hunstig_Hemsel_Sextro_2012, title={An efficient simulation technique for high-frequency piezoelectric inertia motors}, DOI={10.1109/ULTSYM.2012.0068}, booktitle={Ultrasonics Symposium (IUS), 2012 IEEE International}, author={Hunstig, Matthias and Hemsel, Tobias and Sextro, Walter}, year={2012}, pages={277–280} }","apa":"Hunstig, M., Hemsel, T., & Sextro, W. (2012). An efficient simulation technique for high-frequency piezoelectric inertia motors. In Ultrasonics Symposium (IUS), 2012 IEEE International (pp. 277–280). https://doi.org/10.1109/ULTSYM.2012.0068","ama":"Hunstig M, Hemsel T, Sextro W. An efficient simulation technique for high-frequency piezoelectric inertia motors. In: Ultrasonics Symposium (IUS), 2012 IEEE International. ; 2012:277-280. doi:10.1109/ULTSYM.2012.0068","ieee":"M. Hunstig, T. Hemsel, and W. Sextro, “An efficient simulation technique for high-frequency piezoelectric inertia motors,” in Ultrasonics Symposium (IUS), 2012 IEEE International, 2012, pp. 277–280.","chicago":"Hunstig, Matthias, Tobias Hemsel, and Walter Sextro. “An Efficient Simulation Technique for High-Frequency Piezoelectric Inertia Motors.” In Ultrasonics Symposium (IUS), 2012 IEEE International, 277–80, 2012. https://doi.org/10.1109/ULTSYM.2012.0068."},"page":"277-280","date_updated":"2022-01-06T07:04:20Z","author":[{"first_name":"Matthias","full_name":"Hunstig, Matthias","last_name":"Hunstig"},{"full_name":"Hemsel, Tobias","last_name":"Hemsel","first_name":"Tobias"},{"first_name":"Walter","full_name":"Sextro, Walter","last_name":"Sextro"}],"date_created":"2019-05-13T13:20:17Z","title":"An efficient simulation technique for high-frequency piezoelectric inertia motors","doi":"10.1109/ULTSYM.2012.0068","type":"conference","publication":"Ultrasonics Symposium (IUS), 2012 IEEE International","abstract":[{"lang":"eng","text":"Piezoelectric inertia motors use the inertia of a body to drive it by means of a friction contact in a series of small steps. These motors can operate in ``stick-slip'' or ``slip-slip'' mode, with the fundamental frequency of the driving signal ranging from several Hertz to more than 100 kHz. To predict the motor characteristics, a Coulomb friction model is sufficient in many cases, but numerical simulation requires microscopic time steps. This contribution proposes a much faster simulation technique using one evaluation per period of the excitation signal. The proposed technique produces results very close to those of timestep simulation for ultrasonics inertia motors and allows direct determination of the steady-state velocity of an inertia motor from the motion profile of the driving part. Thus it is a useful simulation technique which can be applied in both analysis and design of inertia motors, especially for parameter studies and optimisation."}],"status":"public","_id":"9784","user_id":"55222","department":[{"_id":"151"}],"keyword":["friction","ultrasonic motors","Coulomb friction model","efficient simulation technique","friction contact","high-frequency piezoelectric inertia motor","motor characteristics prediction","numerical simulation","slip-slip mode","stick-slip mode","time-step simulation","ultrasonic inertia motor","Acceleration","Acoustics","Actuators","Computational modeling","Friction","Numerical models","Steady-state"],"language":[{"iso":"eng"}]},{"date_created":"2019-07-12T05:29:44Z","author":[{"first_name":"Volker","full_name":"Leutnant, Volker","last_name":"Leutnant"},{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"date_updated":"2022-01-06T06:51:11Z","oa":"1","main_file_link":[{"open_access":"1","url":"http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6335731"}],"title":"A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR","citation":{"apa":"Leutnant, V., Krueger, A., & Haeb-Umbach, R. (2012). A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR. In Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on.","mla":"Leutnant, Volker, et al. “A Statistical Observation Model For Noisy Reverberant Speech Features and Its Application to Robust ASR.” Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.","short":"V. Leutnant, A. Krueger, R. Haeb-Umbach, in: Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.","bibtex":"@inproceedings{Leutnant_Krueger_Haeb-Umbach_2012, title={A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR}, booktitle={Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on}, author={Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2012} }","ama":"Leutnant V, Krueger A, Haeb-Umbach R. A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR. In: Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On. ; 2012.","ieee":"V. Leutnant, A. Krueger, and R. Haeb-Umbach, “A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR,” in Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on, 2012.","chicago":"Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “A Statistical Observation Model For Noisy Reverberant Speech Features and Its Application to Robust ASR.” In Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On, 2012."},"year":"2012","user_id":"44006","department":[{"_id":"54"}],"_id":"11864","language":[{"iso":"eng"}],"keyword":["Robust Automatic Speech Recognition","Bayesian feature enhancement","observation model for reverberant and noisy speech"],"type":"conference","publication":"Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on","status":"public","abstract":[{"text":"In this work, an observation model for the joint compensation of noise and reverberation in the logarithmic mel power spectral density domain is considered. It relates the features of the noisy reverberant speech to those of the non-reverberant speech and the noise. In contrast to enhancement of features only corrupted by reverberation (reverberant features), enhancement of noisy reverberant features requires a more sophisticated model for the error introduced by the proposed observation model. In a first consideration, it will be shown that this error is highly dependent on the instantaneous ratio of the power of reverberant speech to the power of the noise and, moreover, sensitive to the phase between reverberant speech and noise in the short-time discrete Fourier domain. Afterwards, a statistically motivated approach will be presented allowing for the model of the observation error to be inferred from the error model previously used for the reverberation only case. Finally, the developed observation error model will be utilized in a Bayesian feature enhancement scheme, leading to improvements in word accuracy on the AURORA5 database.","lang":"eng"}]},{"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)","type":"conference","status":"public","abstract":[{"text":"The paper proposes a modification of the standard maximum a posteriori (MAP) method for the estimation of the parameters of a Gaussian process for cases where the process is superposed by additive Gaussian observation errors of known variance. Simulations on artificially generated data demonstrate the superiority of the proposed method. While reducing to the ordinary MAP approach in the absence of observation noise, the improvement becomes the more pronounced the larger the variance of the observation noise. The method is further extended to track the parameters in case of non-stationary Gaussian processes.","lang":"eng"}],"department":[{"_id":"54"}],"user_id":"44006","_id":"11845","language":[{"iso":"eng"}],"keyword":["Gaussian processes","MAP-based estimation","maximum a posteriori method","maximum likelihood estimation","nonstationary Gaussian processes"],"page":"3596-3599","citation":{"ama":"Krueger A, Haeb-Umbach R. MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011). ; 2011:3596-3599. doi:10.1109/ICASSP.2011.5946256","chicago":"Krueger, Alexander, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of Non-Stationary Gaussian Processes from Noisy Observations.” In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 3596–99, 2011. https://doi.org/10.1109/ICASSP.2011.5946256.","ieee":"A. Krueger and R. Haeb-Umbach, “MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.","apa":"Krueger, A., & Haeb-Umbach, R. (2011). MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) (pp. 3596–3599). https://doi.org/10.1109/ICASSP.2011.5946256","bibtex":"@inproceedings{Krueger_Haeb-Umbach_2011, title={MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations}, DOI={10.1109/ICASSP.2011.5946256}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011)}, author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2011}, pages={3596–3599} }","short":"A. Krueger, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–3599.","mla":"Krueger, Alexander, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of Non-Stationary Gaussian Processes from Noisy Observations.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011), 2011, pp. 3596–99, doi:10.1109/ICASSP.2011.5946256."},"year":"2011","date_created":"2019-07-12T05:29:22Z","author":[{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach"}],"oa":"1","date_updated":"2022-01-06T06:51:11Z","doi":"10.1109/ICASSP.2011.5946256","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2011/KrHa11.pdf"}],"title":"MAP-based estimation of the parameters of non-stationary Gaussian processes from noisy observations"},{"citation":{"apa":"Krueger, A., Warsitz, E., & Haeb-Umbach, R. (2011). Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions on Audio, Speech, and Language Processing, 19(1), 206–219. https://doi.org/10.1109/TASL.2010.2047324","mla":"Krueger, Alexander, et al. “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, 2011, pp. 206–19, doi:10.1109/TASL.2010.2047324.","bibtex":"@article{Krueger_Warsitz_Haeb-Umbach_2011, title={Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation}, volume={19}, DOI={10.1109/TASL.2010.2047324}, number={1}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2011}, pages={206–219} }","short":"A. Krueger, E. Warsitz, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 19 (2011) 206–219.","chicago":"Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation.” IEEE Transactions on Audio, Speech, and Language Processing 19, no. 1 (2011): 206–19. https://doi.org/10.1109/TASL.2010.2047324.","ieee":"A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 19, no. 1, pp. 206–219, 2011.","ama":"Krueger A, Warsitz E, Haeb-Umbach R. Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. IEEE Transactions on Audio, Speech, and Language Processing. 2011;19(1):206-219. doi:10.1109/TASL.2010.2047324"},"page":"206-219","intvolume":" 19","date_updated":"2022-01-06T06:51:11Z","oa":"1","author":[{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"last_name":"Warsitz","full_name":"Warsitz, Ernst","first_name":"Ernst"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"volume":19,"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2011/KrWaHa11.pdf"}],"doi":"10.1109/TASL.2010.2047324","type":"journal_article","status":"public","_id":"11850","user_id":"44006","department":[{"_id":"54"}],"issue":"1","year":"2011","date_created":"2019-07-12T05:29:28Z","title":"Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation","publication":"IEEE Transactions on Audio, Speech, and Language Processing","abstract":[{"text":"In this paper, we present a novel blocking matrix and fixed beamformer design for a generalized sidelobe canceler for speech enhancement in a reverberant enclosure. They are based on a new method for estimating the acoustical transfer function ratios in the presence of stationary noise. The estimation method relies on solving a generalized eigenvalue problem in each frequency bin. An adaptive eigenvector tracking utilizing the power iteration method is employed and shown to achieve a high convergence speed. Simulation results demonstrate that the proposed beamformer leads to better noise and interference reduction and reduced speech distortions compared to other blocking matrix designs from the literature.","lang":"eng"}],"keyword":["acoustical transfer function ratio","adaptive eigenvector tracking","array signal processing","beamformer design","blocking matrix","eigenvalues and eigenfunctions","eigenvector-based transfer function ratios estimation","generalized sidelobe canceler","interference reduction","iterative methods","power iteration method","reduced speech distortions","reverberant enclosure","reverberation","speech enhancement","stationary noise"],"language":[{"iso":"eng"}]},{"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"}],"publication":"IEEE Transactions on Audio, Speech, and Language Processing","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"],"language":[{"iso":"eng"}],"year":"2010","issue":"7","title":"Model-Based Feature Enhancement for Reverberant Speech Recognition","date_created":"2019-07-12T05:29:23Z","status":"public","type":"journal_article","_id":"11846","department":[{"_id":"54"}],"user_id":"44006","page":"1692-1707","intvolume":" 18","citation":{"apa":"Krueger, A., & Haeb-Umbach, R. (2010). Model-Based Feature Enhancement for Reverberant Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 18(7), 1692–1707. https://doi.org/10.1109/TASL.2010.2049684","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.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 7, 2010, pp. 1692–707, doi:10.1109/TASL.2010.2049684.","bibtex":"@article{Krueger_Haeb-Umbach_2010, title={Model-Based Feature Enhancement for Reverberant Speech Recognition}, volume={18}, DOI={10.1109/TASL.2010.2049684}, number={7}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2010}, pages={1692–1707} }","chicago":"Krueger, Alexander, and Reinhold Haeb-Umbach. “Model-Based Feature Enhancement for Reverberant Speech Recognition.” IEEE Transactions on Audio, Speech, and Language Processing 18, no. 7 (2010): 1692–1707. https://doi.org/10.1109/TASL.2010.2049684.","ieee":"A. Krueger and R. Haeb-Umbach, “Model-Based Feature Enhancement for Reverberant Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 18, no. 7, pp. 1692–1707, 2010.","ama":"Krueger A, Haeb-Umbach R. Model-Based Feature Enhancement for Reverberant Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing. 2010;18(7):1692-1707. doi:10.1109/TASL.2010.2049684"},"doi":"10.1109/TASL.2010.2049684","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2010/KrHa10.pdf"}],"oa":"1","date_updated":"2022-01-06T06:51:11Z","volume":18,"author":[{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach"}]},{"citation":{"bibtex":"@inproceedings{Tran Vu_Haeb-Umbach_2010, title={Blind speech separation employing directional statistics in an Expectation Maximization framework}, DOI={10.1109/ICASSP.2010.5495994}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2010}, pages={241–244} }","short":"D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.","mla":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing Directional Statistics in an Expectation Maximization Framework.” IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–44, doi:10.1109/ICASSP.2010.5495994.","apa":"Tran Vu, D. H., & Haeb-Umbach, R. (2010). Blind speech separation employing directional statistics in an Expectation Maximization framework. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010) (pp. 241–244). https://doi.org/10.1109/ICASSP.2010.5495994","ieee":"D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional statistics in an Expectation Maximization framework,” in IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.","chicago":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing Directional Statistics in an Expectation Maximization Framework.” In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 241–44, 2010. https://doi.org/10.1109/ICASSP.2010.5495994.","ama":"Tran Vu DH, Haeb-Umbach R. Blind speech separation employing directional statistics in an Expectation Maximization framework. In: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010). ; 2010:241-244. doi:10.1109/ICASSP.2010.5495994"},"page":"241-244","year":"2010","author":[{"full_name":"Tran Vu, Dang Hai","last_name":"Tran Vu","first_name":"Dang Hai"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"date_created":"2019-07-12T05:30:40Z","oa":"1","date_updated":"2022-01-06T06:51:12Z","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf","open_access":"1"}],"doi":"10.1109/ICASSP.2010.5495994","title":"Blind speech separation employing directional statistics in an Expectation Maximization framework","type":"conference","publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)","status":"public","abstract":[{"lang":"eng","text":"In this paper we propose to employ directional statistics in a complex vector space to approach the problem of blind speech separation in the presence of spatially correlated noise. We interpret the values of the short time Fourier transform of the microphone signals to be draws from a mixture of complex Watson distributions, a probabilistic model which naturally accounts for spatial aliasing. The parameters of the density are related to the a priori source probabilities, the power of the sources and the transfer function ratios from sources to sensors. Estimation formulas are derived for these parameters by employing the Expectation Maximization (EM) algorithm. The E-step corresponds to the estimation of the source presence probabilities for each time-frequency bin, while the M-step leads to a maximum signal-to-noise ratio (MaxSNR) beamformer in the presence of uncertainty about the source activity. Experimental results are reported for an implementation in a generalized sidelobe canceller (GSC) like spatial beamforming configuration for 3 speech sources with significant coherent noise in reverberant environments, demonstrating the usefulness of the novel modeling framework."}],"user_id":"44006","department":[{"_id":"54"}],"_id":"11913","language":[{"iso":"eng"}],"keyword":["array signal processing","blind source separation","blind speech separation","complex vector space","complex Watson distribution","directional statistics","expectation-maximisation algorithm","expectation maximization algorithm","Fourier transform","Fourier transforms","generalized sidelobe canceller","interference suppression","maximum signal-to-noise ratio beamformer","microphone signal","probabilistic model","spatial aliasing","spatial beamforming configuration","speech enhancement","statistical distributions"]},{"type":"conference","publication":"Proceedings of DATE’10","status":"public","abstract":[{"text":"Today we can identify a big gap between requirement specification and the generation of test environments. This article extends the Classification Tree Method for Embedded Systems (CTM/ES) to fill this gap by new concepts for the precise specification of stimuli for operational ranges of continuous control systems. It introduces novel means for continuous acceptance criteria definition and for functional coverage definition.","lang":"eng"}],"user_id":"5786","department":[{"_id":"672"}],"_id":"37037","language":[{"iso":"eng"}],"keyword":["System testing","Automatic testing","Object oriented modeling","Classification tree analysis","Automotive engineering","Mathematical model","Embedded system","Control systems","Electronic equipment testing","Software testing"],"citation":{"ieee":"A. Krupp and W. Müller, “A Systematic Approach to Combined HW/SW System Test,” presented at the Design, Automation & Test in Europe Conference & Exhibition (DATE 2010), Dresden, 2010, doi: 10.1109/DATE.2010.5457186.","chicago":"Krupp, Alexander, and Wolfgang Müller. “A Systematic Approach to Combined HW/SW System Test.” In Proceedings of DATE’10. Dresden: IEEE, 2010. https://doi.org/10.1109/DATE.2010.5457186.","ama":"Krupp A, Müller W. A Systematic Approach to Combined HW/SW System Test. In: Proceedings of DATE’10. IEEE; 2010. doi:10.1109/DATE.2010.5457186","short":"A. Krupp, W. Müller, in: Proceedings of DATE’10, IEEE, Dresden, 2010.","mla":"Krupp, Alexander, and Wolfgang Müller. “A Systematic Approach to Combined HW/SW System Test.” Proceedings of DATE’10, IEEE, 2010, doi:10.1109/DATE.2010.5457186.","bibtex":"@inproceedings{Krupp_Müller_2010, place={Dresden}, title={A Systematic Approach to Combined HW/SW System Test}, DOI={10.1109/DATE.2010.5457186}, booktitle={Proceedings of DATE’10}, publisher={IEEE}, author={Krupp, Alexander and Müller, Wolfgang}, year={2010} }","apa":"Krupp, A., & Müller, W. (2010). A Systematic Approach to Combined HW/SW System Test. Proceedings of DATE’10. Design, Automation & Test in Europe Conference & Exhibition (DATE 2010), Dresden. https://doi.org/10.1109/DATE.2010.5457186"},"year":"2010","place":"Dresden","author":[{"first_name":"Alexander","last_name":"Krupp","full_name":"Krupp, Alexander"},{"first_name":"Wolfgang","full_name":"Müller, Wolfgang","id":"16243","last_name":"Müller"}],"date_created":"2023-01-17T10:41:15Z","publisher":"IEEE","date_updated":"2023-01-17T10:41:25Z","conference":{"name":"Design, Automation & Test in Europe Conference & Exhibition (DATE 2010)","location":"Dresden"},"doi":"10.1109/DATE.2010.5457186","title":"A Systematic Approach to Combined HW/SW System Test"},{"date_updated":"2023-01-17T11:35:03Z","publisher":"IEEE","author":[{"first_name":"Gilles B.","full_name":"Defo, Gilles B.","last_name":"Defo"},{"last_name":"Müller","full_name":"Müller, Wolfgang","id":"16243","first_name":"Wolfgang"},{"full_name":"Kuznik, Christoph","last_name":"Kuznik","first_name":"Christoph"}],"date_created":"2023-01-17T11:34:56Z","title":"Verification of a CAN Bus Model in SystemC with Functional Coverage","conference":{"location":" Trento, Italy","name":"International Symposium on Industrial Embedded System (SIES)"},"doi":"10.1109/SIES.2010.5551379","publication_identifier":{"eisbn":["978-1-4244-5841-7"]},"place":" Trento, Italy","year":"2010","citation":{"mla":"Defo, Gilles B., et al. “Verification of a CAN Bus Model in SystemC with Functional Coverage.” Proceedings of SIES 2010, IEEE, 2010, doi:10.1109/SIES.2010.5551379.","bibtex":"@inproceedings{Defo_Müller_Kuznik_2010, place={ Trento, Italy}, title={Verification of a CAN Bus Model in SystemC with Functional Coverage}, DOI={10.1109/SIES.2010.5551379}, booktitle={Proceedings of SIES 2010}, publisher={IEEE}, author={Defo, Gilles B. and Müller, Wolfgang and Kuznik, Christoph}, year={2010} }","short":"G.B. Defo, W. Müller, C. Kuznik, in: Proceedings of SIES 2010, IEEE, Trento, Italy, 2010.","apa":"Defo, G. B., Müller, W., & Kuznik, C. (2010). Verification of a CAN Bus Model in SystemC with Functional Coverage. Proceedings of SIES 2010. International Symposium on Industrial Embedded System (SIES), Trento, Italy. https://doi.org/10.1109/SIES.2010.5551379","chicago":"Defo, Gilles B., Wolfgang Müller, and Christoph Kuznik. “Verification of a CAN Bus Model in SystemC with Functional Coverage.” In Proceedings of SIES 2010. Trento, Italy: IEEE, 2010. https://doi.org/10.1109/SIES.2010.5551379.","ieee":"G. B. Defo, W. Müller, and C. Kuznik, “Verification of a CAN Bus Model in SystemC with Functional Coverage,” presented at the International Symposium on Industrial Embedded System (SIES), Trento, Italy, 2010, doi: 10.1109/SIES.2010.5551379.","ama":"Defo GB, Müller W, Kuznik C. Verification of a CAN Bus Model in SystemC with Functional Coverage. In: Proceedings of SIES 2010. IEEE; 2010. doi:10.1109/SIES.2010.5551379"},"_id":"37057","department":[{"_id":"672"}],"user_id":"5786","keyword":["Libraries","Generators","Transfer functions","Monitoring","Computational modeling","Driver circuits","Adaptation model"],"language":[{"iso":"eng"}],"publication":"Proceedings of SIES 2010","type":"conference","abstract":[{"lang":"eng","text":"Many heterogeneous embedded systems, for example industrial automation and automotive applications, require hard-real time constraints to be exhaustively verified - which is a challenging task for the verification engineer. To cope with complexity, verification techniques working on different abstraction levels are best practice. SystemC is a versatile C++ based design and verification language, offering various mechanisms and constructs required for embedded systems modeling. Using the add-on SystemC Verification Library (SCV) elemental constrained-random stimuli techniques may be used for verification. However, SCV has several drawbacks such as lack of functional coverage. In this paper we present a functional coverage library that implements parts of the IEEE 1800-2005 SystemVerilog standard and allows capturing functional coverage throughout the design and verification process with SystemC. Moreover, we will demonstrate the usability of the approach with a case study working on a CAN bus model written in SystemC."}],"status":"public"},{"_id":"11723","user_id":"44006","department":[{"_id":"54"}],"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"],"language":[{"iso":"eng"}],"type":"conference","publication":"6th Workshop on Positioning Navigation and Communication (WPNC 2009)","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"}],"status":"public","oa":"1","date_updated":"2022-01-06T06:51:07Z","author":[{"full_name":"Bevermeier, Maik","last_name":"Bevermeier","first_name":"Maik"},{"first_name":"Sven","last_name":"Peschke","full_name":"Peschke, Sven"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"date_created":"2019-07-12T05:27:01Z","title":"Robust vehicle localization based on multi-level sensor fusion and online parameter estimation","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2009/BePeHa09.pdf"}],"doi":"10.1109/WPNC.2009.4907833","year":"2009","citation":{"mla":"Bevermeier, Maik, et al. “Robust Vehicle Localization Based on Multi-Level Sensor Fusion and Online Parameter Estimation.” 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp. 235–42, doi:10.1109/WPNC.2009.4907833.","bibtex":"@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Robust vehicle localization based on multi-level sensor fusion and online parameter estimation}, DOI={10.1109/WPNC.2009.4907833}, 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} }","short":"M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp. 235–242.","apa":"Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Robust vehicle localization based on multi-level sensor fusion and online parameter estimation. In 6th Workshop on Positioning Navigation and Communication (WPNC 2009) (pp. 235–242). https://doi.org/10.1109/WPNC.2009.4907833","chicago":"Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Robust Vehicle Localization Based on Multi-Level Sensor Fusion and Online Parameter Estimation.” In 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 235–42, 2009. https://doi.org/10.1109/WPNC.2009.4907833.","ieee":"M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Robust vehicle localization based on multi-level sensor fusion and online parameter estimation,” in 6th Workshop on Positioning Navigation and Communication (WPNC 2009), 2009, pp. 235–242.","ama":"Bevermeier M, Peschke S, Haeb-Umbach R. Robust vehicle localization based on multi-level sensor fusion and online parameter estimation. In: 6th Workshop on Positioning Navigation and Communication (WPNC 2009). ; 2009:235-242. doi:10.1109/WPNC.2009.4907833"},"page":"235-242"},{"year":"2009","page":"1-5","citation":{"ama":"Bevermeier M, Peschke S, Haeb-Umbach R. Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning. In: IEEE 69th Vehicular Technology Conference (VTC 2009 Spring). ; 2009:1-5. doi:10.1109/VETECS.2009.5073634","chicago":"Bevermeier, Maik, Sven Peschke, and Reinhold Haeb-Umbach. “Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.” In IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 1–5, 2009. https://doi.org/10.1109/VETECS.2009.5073634.","ieee":"M. Bevermeier, S. Peschke, and R. Haeb-Umbach, “Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning,” in IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5.","mla":"Bevermeier, Maik, et al. “Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning.” IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5, doi:10.1109/VETECS.2009.5073634.","bibtex":"@inproceedings{Bevermeier_Peschke_Haeb-Umbach_2009, title={Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning}, DOI={10.1109/VETECS.2009.5073634}, booktitle={IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)}, author={Bevermeier, Maik and Peschke, Sven and Haeb-Umbach, Reinhold}, year={2009}, pages={1–5} }","short":"M. Bevermeier, S. Peschke, R. Haeb-Umbach, in: IEEE 69th Vehicular Technology Conference (VTC 2009 Spring), 2009, pp. 1–5.","apa":"Bevermeier, M., Peschke, S., & Haeb-Umbach, R. (2009). Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning. In IEEE 69th Vehicular Technology Conference (VTC 2009 Spring) (pp. 1–5). https://doi.org/10.1109/VETECS.2009.5073634"},"title":"Joint Parameter Estimation and Tracking in a Multi-Stage Kalman Filter for Vehicle Positioning","doi":"10.1109/VETECS.2009.5073634","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","oa":"1","date_created":"2019-07-12T05:27:02Z","author":[{"last_name":"Bevermeier","full_name":"Bevermeier, Maik","first_name":"Maik"},{"full_name":"Peschke, Sven","last_name":"Peschke","first_name":"Sven"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"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."}],"status":"public","publication":"IEEE 69th Vehicular Technology Conference (VTC 2009 Spring)","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"],"language":[{"iso":"eng"}],"_id":"11724","department":[{"_id":"54"}],"user_id":"44006"},{"issue":"5","year":"2009","date_created":"2019-07-12T05:31:08Z","title":"Approaches to Iterative Speech Feature Enhancement and Recognition","publication":"IEEE Transactions on Audio, Speech, and Language Processing","abstract":[{"lang":"eng","text":"In automatic speech recognition, hidden Markov models (HMMs) are commonly used for speech decoding, while switching linear dynamic models (SLDMs) can be employed for a preceding model-based speech feature enhancement. In this paper, these model types are combined in order to obtain a novel iterative speech feature enhancement and recognition architecture. It is shown that speech feature enhancement with SLDMs can be improved by feeding back information from the HMM to the enhancement stage. Two different feedback structures are derived. In the first, the posteriors of the HMM states are used to control the model probabilities of the SLDMs, while in the second they are employed to directly influence the estimate of the speech feature distribution. Both approaches lead to improvements in recognition accuracy both on the AURORA2 and AURORA4 databases compared to non-iterative speech feature enhancement with SLDMs. It is also shown that a combination with uncertainty decoding further enhances performance."}],"language":[{"iso":"eng"}],"keyword":["AURORA2 databases","AURORA4 databases","automatic speech recognition","feedback structures","hidden Markov models","HMM","iterative methods","iterative speech feature enhancement","model probabilities","speech decoding","speech enhancement","speech feature distribution","speech recognition","switching linear dynamic models"],"citation":{"bibtex":"@article{Windmann_Haeb-Umbach_2009, title={Approaches to Iterative Speech Feature Enhancement and Recognition}, volume={17}, DOI={10.1109/TASL.2009.2014894}, number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={974–984} }","mla":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech Feature Enhancement and Recognition.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 17, no. 5, 2009, pp. 974–84, doi:10.1109/TASL.2009.2014894.","short":"S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 17 (2009) 974–984.","apa":"Windmann, S., & Haeb-Umbach, R. (2009). Approaches to Iterative Speech Feature Enhancement and Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 17(5), 974–984. https://doi.org/10.1109/TASL.2009.2014894","ama":"Windmann S, Haeb-Umbach R. Approaches to Iterative Speech Feature Enhancement and Recognition. IEEE Transactions on Audio, Speech, and Language Processing. 2009;17(5):974-984. doi:10.1109/TASL.2009.2014894","chicago":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech Feature Enhancement and Recognition.” IEEE Transactions on Audio, Speech, and Language Processing 17, no. 5 (2009): 974–84. https://doi.org/10.1109/TASL.2009.2014894.","ieee":"S. Windmann and R. Haeb-Umbach, “Approaches to Iterative Speech Feature Enhancement and Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 17, no. 5, pp. 974–984, 2009."},"page":"974-984","intvolume":" 17","author":[{"first_name":"Stefan","last_name":"Windmann","full_name":"Windmann, Stefan"},{"last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242","first_name":"Reinhold"}],"volume":17,"date_updated":"2022-01-06T06:51:12Z","oa":"1","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-1.pdf","open_access":"1"}],"doi":"10.1109/TASL.2009.2014894","type":"journal_article","status":"public","user_id":"44006","department":[{"_id":"54"}],"_id":"11937"},{"issue":"8","page":"1577-1590","intvolume":" 17","citation":{"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.” IEEE Transactions on Audio, Speech, and Language Processing, vol. 17, no. 8, 2009, pp. 1577–90, doi:10.1109/TASL.2009.2023172.","bibtex":"@article{Windmann_Haeb-Umbach_2009, title={Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition}, volume={17}, DOI={10.1109/TASL.2009.2023172}, number={8}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={1577–1590} }","apa":"Windmann, S., & Haeb-Umbach, R. (2009). Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing, 17(8), 1577–1590. https://doi.org/10.1109/TASL.2009.2023172","chicago":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition.” IEEE Transactions on Audio, Speech, and Language Processing 17, no. 8 (2009): 1577–90. https://doi.org/10.1109/TASL.2009.2023172.","ieee":"S. Windmann and R. Haeb-Umbach, “Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition,” IEEE Transactions on Audio, Speech, and Language Processing, vol. 17, no. 8, pp. 1577–1590, 2009.","ama":"Windmann S, Haeb-Umbach R. Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition. IEEE Transactions on Audio, Speech, and Language Processing. 2009;17(8):1577-1590. doi:10.1109/TASL.2009.2023172"},"year":"2009","volume":17,"date_created":"2019-07-12T05:31:09Z","author":[{"first_name":"Stefan","full_name":"Windmann, Stefan","last_name":"Windmann"},{"full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"oa":"1","date_updated":"2022-01-06T06:51:12Z","doi":"10.1109/TASL.2009.2023172","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-2.pdf"}],"title":"Parameter Estimation of a State-Space Model of Noise for Robust Speech Recognition","publication":"IEEE Transactions on Audio, Speech, and Language Processing","type":"journal_article","status":"public","abstract":[{"lang":"eng","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."}],"department":[{"_id":"54"}],"user_id":"44006","_id":"11938","language":[{"iso":"eng"}],"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"]}]