[{"project":[{"_id":"130","name":"TRR 285: TRR 285:  Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen Prozessketten","grant_number":"418701707"},{"_id":"131","name":"TRR 285 - A: TRR 285 - Project Area A"},{"_id":"139","name":"TRR 285 – A05: TRR 285 - Subproject A05"}],"_id":"58492","user_id":"84990","article_type":"original","article_number":"106026","type":"journal_article","status":"public","date_updated":"2025-01-31T17:06:22Z","author":[{"first_name":"Johannes","last_name":"Friedlein","full_name":"Friedlein, Johannes"},{"full_name":"Mergheim, Julia","last_name":"Mergheim","first_name":"Julia"},{"last_name":"Steinmann","full_name":"Steinmann, Paul","first_name":"Paul"}],"volume":196,"doi":"10.1016/j.jmps.2025.106026","publication_status":"published","publication_identifier":{"issn":["0022-5096"]},"citation":{"bibtex":"@article{Friedlein_Mergheim_Steinmann_2025, title={Modelling of stress-state-dependent ductile damage with gradient-enhancement exemplified for clinch joining}, volume={196}, DOI={<a href=\"https://doi.org/10.1016/j.jmps.2025.106026\">10.1016/j.jmps.2025.106026</a>}, number={106026}, journal={Journal of the Mechanics and Physics of Solids}, publisher={Elsevier BV}, author={Friedlein, Johannes and Mergheim, Julia and Steinmann, Paul}, year={2025} }","mla":"Friedlein, Johannes, et al. “Modelling of Stress-State-Dependent Ductile Damage with Gradient-Enhancement Exemplified for Clinch Joining.” <i>Journal of the Mechanics and Physics of Solids</i>, vol. 196, 106026, Elsevier BV, 2025, doi:<a href=\"https://doi.org/10.1016/j.jmps.2025.106026\">10.1016/j.jmps.2025.106026</a>.","short":"J. Friedlein, J. Mergheim, P. Steinmann, Journal of the Mechanics and Physics of Solids 196 (2025).","apa":"Friedlein, J., Mergheim, J., &#38; Steinmann, P. (2025). Modelling of stress-state-dependent ductile damage with gradient-enhancement exemplified for clinch joining. <i>Journal of the Mechanics and Physics of Solids</i>, <i>196</i>, Article 106026. <a href=\"https://doi.org/10.1016/j.jmps.2025.106026\">https://doi.org/10.1016/j.jmps.2025.106026</a>","chicago":"Friedlein, Johannes, Julia Mergheim, and Paul Steinmann. “Modelling of Stress-State-Dependent Ductile Damage with Gradient-Enhancement Exemplified for Clinch Joining.” <i>Journal of the Mechanics and Physics of Solids</i> 196 (2025). <a href=\"https://doi.org/10.1016/j.jmps.2025.106026\">https://doi.org/10.1016/j.jmps.2025.106026</a>.","ieee":"J. Friedlein, J. Mergheim, and P. Steinmann, “Modelling of stress-state-dependent ductile damage with gradient-enhancement exemplified for clinch joining,” <i>Journal of the Mechanics and Physics of Solids</i>, vol. 196, Art. no. 106026, 2025, doi: <a href=\"https://doi.org/10.1016/j.jmps.2025.106026\">10.1016/j.jmps.2025.106026</a>.","ama":"Friedlein J, Mergheim J, Steinmann P. Modelling of stress-state-dependent ductile damage with gradient-enhancement exemplified for clinch joining. <i>Journal of the Mechanics and Physics of Solids</i>. 2025;196. doi:<a href=\"https://doi.org/10.1016/j.jmps.2025.106026\">10.1016/j.jmps.2025.106026</a>"},"intvolume":"       196","keyword":["Finite plasticity","Ductile damage","Gradient-enhancement","Stress-state dependency","Failure"],"language":[{"iso":"eng"}],"publication":"Journal of the Mechanics and Physics of Solids","abstract":[{"text":"A coupled finite plasticity ductile damage and failure model is proposed for the finite element simulation of clinch joining, which incorporates stress-state dependency and regularisation by gradient-enhancement of the damage variable. Ductile damage is determined based on a failure indicator governed by a failure surface in stress space. The latter is exemplary chosen as a combination of the Hosford–Coulomb and Cockcroft–Latham–Oh failure criteria for the high and low stress triaxiality range, respectively, to cover the wide stress range encountered in forming. Damage is coupled to elasto-plasticity to capture the damage-induced degradation of the stiffness and flow stress. This affects the material behaviour up to failure, thereby realistically altering the stress state. Consequently, especially for highly ductile materials, where substantial necking and localisation precede material fracture, the failure prediction is enhanced. The resulting stress softening is regularised by gradient-enhancement to obtain mesh-objective results. The analysis of a modified punch test experiment emphasises how the damage-induced softening effect can strongly alter the actual stress state towards failure. Moreover, the impact of successful regularisation is shown, and the applicability of the damage and failure model to clinch joining is proven.","lang":"eng"}],"publisher":"Elsevier BV","date_created":"2025-01-31T17:04:12Z","title":"Modelling of stress-state-dependent ductile damage with gradient-enhancement exemplified for clinch joining","year":"2025"},{"_id":"63988","user_id":"100715","keyword":["solid-state nmr","dynamic nuclear polarization","Hydroxypropyl cellulose","Selective enhancement","Spin labelling"],"language":[{"iso":"eng"}],"extern":"1","type":"journal_article","publication":"Journal of Magnetic Resonance Open","abstract":[{"lang":"eng","text":"This concept summarizes recent advances in development and application of DNP enhanced multinuclear solid-state NMR to study the molecular structure and surface functionalization of cellulose and paper-based materials. Moreover, a novel application is presented where DNP enhanced 13C and 15N solid-state NMR is used to identify structure moieties formed by cross-linking of hydroxypropyl cellulose. Given these two aspects of this concept-type of article, we thus combine both, a review on recent findings already published and unpublished recent data that complement the existing knowledge in the field of characterization of functional lignocellulosic materials by DNP enhanced solid-state NMR."}],"status":"public","date_updated":"2026-02-17T16:16:40Z","date_created":"2026-02-07T15:46:32Z","author":[{"last_name":"Höfler","full_name":"Höfler, Mark V.","first_name":"Mark V."},{"first_name":"Jonas","full_name":"Lins, Jonas","last_name":"Lins"},{"last_name":"Seelinger","full_name":"Seelinger, David","first_name":"David"},{"full_name":"Pachernegg, Lukas","last_name":"Pachernegg","first_name":"Lukas"},{"first_name":"Timmy","last_name":"Schäfer","full_name":"Schäfer, Timmy"},{"full_name":"Spirk, Stefan","last_name":"Spirk","first_name":"Stefan"},{"last_name":"Biesalski","full_name":"Biesalski, Markus","first_name":"Markus"},{"first_name":"Torsten","id":"118165","full_name":"Gutmann, Torsten","last_name":"Gutmann"}],"volume":21,"title":"DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization of cellulose/paper derived materials","doi":"10.1016/j.jmro.2024.100163","year":"2024","citation":{"apa":"Höfler, M. V., Lins, J., Seelinger, D., Pachernegg, L., Schäfer, T., Spirk, S., Biesalski, M., &#38; Gutmann, T. (2024). DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization of cellulose/paper derived materials. <i>Journal of Magnetic Resonance Open</i>, <i>21</i>, 100163. <a href=\"https://doi.org/10.1016/j.jmro.2024.100163\">https://doi.org/10.1016/j.jmro.2024.100163</a>","mla":"Höfler, Mark V., et al. “DNP Enhanced Solid-State NMR – A Powerful Tool to Address the Surface Functionalization of Cellulose/Paper Derived Materials.” <i>Journal of Magnetic Resonance Open</i>, vol. 21, 2024, p. 100163, doi:<a href=\"https://doi.org/10.1016/j.jmro.2024.100163\">10.1016/j.jmro.2024.100163</a>.","short":"M.V. Höfler, J. Lins, D. Seelinger, L. Pachernegg, T. Schäfer, S. Spirk, M. Biesalski, T. Gutmann, Journal of Magnetic Resonance Open 21 (2024) 100163.","bibtex":"@article{Höfler_Lins_Seelinger_Pachernegg_Schäfer_Spirk_Biesalski_Gutmann_2024, title={DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization of cellulose/paper derived materials}, volume={21}, DOI={<a href=\"https://doi.org/10.1016/j.jmro.2024.100163\">10.1016/j.jmro.2024.100163</a>}, journal={Journal of Magnetic Resonance Open}, author={Höfler, Mark V. and Lins, Jonas and Seelinger, David and Pachernegg, Lukas and Schäfer, Timmy and Spirk, Stefan and Biesalski, Markus and Gutmann, Torsten}, year={2024}, pages={100163} }","ama":"Höfler MV, Lins J, Seelinger D, et al. DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization of cellulose/paper derived materials. <i>Journal of Magnetic Resonance Open</i>. 2024;21:100163. doi:<a href=\"https://doi.org/10.1016/j.jmro.2024.100163\">10.1016/j.jmro.2024.100163</a>","ieee":"M. V. Höfler <i>et al.</i>, “DNP enhanced solid-state NMR – A powerful tool to address the surface functionalization of cellulose/paper derived materials,” <i>Journal of Magnetic Resonance Open</i>, vol. 21, p. 100163, 2024, doi: <a href=\"https://doi.org/10.1016/j.jmro.2024.100163\">10.1016/j.jmro.2024.100163</a>.","chicago":"Höfler, Mark V., Jonas Lins, David Seelinger, Lukas Pachernegg, Timmy Schäfer, Stefan Spirk, Markus Biesalski, and Torsten Gutmann. “DNP Enhanced Solid-State NMR – A Powerful Tool to Address the Surface Functionalization of Cellulose/Paper Derived Materials.” <i>Journal of Magnetic Resonance Open</i> 21 (2024): 100163. <a href=\"https://doi.org/10.1016/j.jmro.2024.100163\">https://doi.org/10.1016/j.jmro.2024.100163</a>."},"page":"100163","intvolume":"        21"},{"title":"Efficient gradient enhancements for plasticity with ductile damage in the logarithmic strain space","doi":"10.1016/j.euromechsol.2023.104946","date_updated":"2026-02-24T14:37:05Z","publisher":"Elsevier BV","volume":99,"date_created":"2024-09-10T15:23:49Z","author":[{"full_name":"Friedlein, Johannes","last_name":"Friedlein","first_name":"Johannes"},{"first_name":"Julia","last_name":"Mergheim","full_name":"Mergheim, Julia"},{"full_name":"Steinmann, Paul","last_name":"Steinmann","first_name":"Paul"}],"year":"2023","intvolume":"        99","citation":{"chicago":"Friedlein, Johannes, Julia Mergheim, and Paul Steinmann. “Efficient Gradient Enhancements for Plasticity with Ductile Damage in the Logarithmic Strain Space.” <i>European Journal of Mechanics - A/Solids</i> 99 (2023). <a href=\"https://doi.org/10.1016/j.euromechsol.2023.104946\">https://doi.org/10.1016/j.euromechsol.2023.104946</a>.","ieee":"J. Friedlein, J. Mergheim, and P. Steinmann, “Efficient gradient enhancements for plasticity with ductile damage in the logarithmic strain space,” <i>European Journal of Mechanics - A/Solids</i>, vol. 99, Art. no. 104946, 2023, doi: <a href=\"https://doi.org/10.1016/j.euromechsol.2023.104946\">10.1016/j.euromechsol.2023.104946</a>.","mla":"Friedlein, Johannes, et al. “Efficient Gradient Enhancements for Plasticity with Ductile Damage in the Logarithmic Strain Space.” <i>European Journal of Mechanics - A/Solids</i>, vol. 99, 104946, Elsevier BV, 2023, doi:<a href=\"https://doi.org/10.1016/j.euromechsol.2023.104946\">10.1016/j.euromechsol.2023.104946</a>.","bibtex":"@article{Friedlein_Mergheim_Steinmann_2023, title={Efficient gradient enhancements for plasticity with ductile damage in the logarithmic strain space}, volume={99}, DOI={<a href=\"https://doi.org/10.1016/j.euromechsol.2023.104946\">10.1016/j.euromechsol.2023.104946</a>}, number={104946}, journal={European Journal of Mechanics - A/Solids}, publisher={Elsevier BV}, author={Friedlein, Johannes and Mergheim, Julia and Steinmann, Paul}, year={2023} }","short":"J. Friedlein, J. Mergheim, P. Steinmann, European Journal of Mechanics - A/Solids 99 (2023).","apa":"Friedlein, J., Mergheim, J., &#38; Steinmann, P. (2023). Efficient gradient enhancements for plasticity with ductile damage in the logarithmic strain space. <i>European Journal of Mechanics - A/Solids</i>, <i>99</i>, Article 104946. <a href=\"https://doi.org/10.1016/j.euromechsol.2023.104946\">https://doi.org/10.1016/j.euromechsol.2023.104946</a>","ama":"Friedlein J, Mergheim J, Steinmann P. Efficient gradient enhancements for plasticity with ductile damage in the logarithmic strain space. <i>European Journal of Mechanics - A/Solids</i>. 2023;99. doi:<a href=\"https://doi.org/10.1016/j.euromechsol.2023.104946\">10.1016/j.euromechsol.2023.104946</a>"},"publication_identifier":{"issn":["0997-7538"]},"publication_status":"published","keyword":["Finite plasticity","Logarithmic strain space","Ductile damage","Gradient-enhancement","Gradient-plasticity","Gradient-damage","Loss of ellipticity"],"article_type":"original","article_number":"104946","language":[{"iso":"eng"}],"_id":"56097","project":[{"_id":"130","name":"TRR 285: TRR 285"},{"_id":"131","name":"TRR 285 - A: TRR 285 - Project Area A"},{"_id":"139","name":"TRR 285 – A05: TRR 285 - Subproject A05"},{"_id":"130","name":"TRR 285:  Methodenentwicklung zur mechanischen Fügbarkeit in wandlungsfähigen Prozessketten"}],"user_id":"84990","abstract":[{"lang":"eng","text":"We contrast different gradient-enhancements for plasticity-damage material models in the logarithmic strain space and compare them to reference models based on multiplicative plasticity. The models being compared include plasticity - gradient-damage, where the gradient-enhancement is applied on the local damage variable, and gradient-plasticity - damage with a gradient-enhanced plastic hardening variable. Thereby, gradient-plasticity proved to be able to simultaneously regularise plastic and ductile (plasticity-driven) damage localisation as confirmed by numerical localisation analyses. This appears to be especially advantageous for logarithmic strain space plasticity-damage, because of the observed plastic localisation even for the case of plasticity with hardening. Even though gradient-plasticity appears to be numerically more demanding, two numerical examples indicate a good robustness and mesh objectivity in the softening regime. Moreover, the internal length for plasticity is able to adjust the damage zone width, similarly to gradient-damage, however ensuring a priori that damage takes place exclusively inside the plastic zone."}],"status":"public","publication":"European Journal of Mechanics - A/Solids","type":"journal_article"},{"issue":"7","publication_identifier":{"issn":["1613-7507"]},"intvolume":"        50","page":"895–902","citation":{"short":"S. Hadjiali, R. Savka, M. Plaumann, U. Bommerich, S. Bothe, T. Gutmann, T. Ratajczyk, J. Bernarding, H.H. Limbach, H. Plenio, G. Buntkowsky, Applied Magnetic Resonance 50 (2019) 895–902.","mla":"Hadjiali, S., et al. “Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands.” <i>Applied Magnetic Resonance</i>, vol. 50, no. 7, 2019, pp. 895–902, doi:<a href=\"https://doi.org/10.1007/s00723-019-01115-x\">10.1007/s00723-019-01115-x</a>.","bibtex":"@article{Hadjiali_Savka_Plaumann_Bommerich_Bothe_Gutmann_Ratajczyk_Bernarding_Limbach_Plenio_et al._2019, title={Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands}, volume={50}, DOI={<a href=\"https://doi.org/10.1007/s00723-019-01115-x\">10.1007/s00723-019-01115-x</a>}, number={7}, journal={Applied Magnetic Resonance}, author={Hadjiali, S. and Savka, R. and Plaumann, M. and Bommerich, U. and Bothe, S. and Gutmann, Torsten and Ratajczyk, T. and Bernarding, J. and Limbach, H. H. and Plenio, H. and et al.}, year={2019}, pages={895–902} }","apa":"Hadjiali, S., Savka, R., Plaumann, M., Bommerich, U., Bothe, S., Gutmann, T., Ratajczyk, T., Bernarding, J., Limbach, H. H., Plenio, H., &#38; Buntkowsky, G. (2019). Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands. <i>Applied Magnetic Resonance</i>, <i>50</i>(7), 895–902. <a href=\"https://doi.org/10.1007/s00723-019-01115-x\">https://doi.org/10.1007/s00723-019-01115-x</a>","ama":"Hadjiali S, Savka R, Plaumann M, et al. Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands. <i>Applied Magnetic Resonance</i>. 2019;50(7):895–902. doi:<a href=\"https://doi.org/10.1007/s00723-019-01115-x\">10.1007/s00723-019-01115-x</a>","chicago":"Hadjiali, S., R. Savka, M. Plaumann, U. Bommerich, S. Bothe, Torsten Gutmann, T. Ratajczyk, et al. “Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands.” <i>Applied Magnetic Resonance</i> 50, no. 7 (2019): 895–902. <a href=\"https://doi.org/10.1007/s00723-019-01115-x\">https://doi.org/10.1007/s00723-019-01115-x</a>.","ieee":"S. Hadjiali <i>et al.</i>, “Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands,” <i>Applied Magnetic Resonance</i>, vol. 50, no. 7, pp. 895–902, 2019, doi: <a href=\"https://doi.org/10.1007/s00723-019-01115-x\">10.1007/s00723-019-01115-x</a>."},"year":"2019","volume":50,"date_created":"2026-02-07T15:40:18Z","author":[{"last_name":"Hadjiali","full_name":"Hadjiali, S.","first_name":"S."},{"last_name":"Savka","full_name":"Savka, R.","first_name":"R."},{"first_name":"M.","last_name":"Plaumann","full_name":"Plaumann, M."},{"first_name":"U.","last_name":"Bommerich","full_name":"Bommerich, U."},{"last_name":"Bothe","full_name":"Bothe, S.","first_name":"S."},{"first_name":"Torsten","full_name":"Gutmann, Torsten","id":"118165","last_name":"Gutmann"},{"full_name":"Ratajczyk, T.","last_name":"Ratajczyk","first_name":"T."},{"full_name":"Bernarding, J.","last_name":"Bernarding","first_name":"J."},{"first_name":"H. H.","last_name":"Limbach","full_name":"Limbach, H. H."},{"last_name":"Plenio","full_name":"Plenio, H.","first_name":"H."},{"first_name":"G.","full_name":"Buntkowsky, G.","last_name":"Buntkowsky"}],"date_updated":"2026-02-17T16:17:34Z","doi":"10.1007/s00723-019-01115-x","title":"Substituent Influences on the NMR Signal Amplification of Ir Complexes with Heterocyclic Carbene Ligands","publication":"Applied Magnetic Resonance","type":"journal_article","status":"public","abstract":[{"text":"A number of Ir-N-heterocyclic carbene (Ir-NHC) complexes with asymmetric N-heterocyclic carbene (NHC) ligands have been prepared and examined for signal amplification by reversible exchange (SABRE). Pyridine was chosen as model compound for hyperpolarization experiments. This substrate was examined in a solvent mixture using several Ir-NHC complexes, which differ in their NHC ligands. The SABRE polarization was created at 6mT and the H-1 nuclear magnetic resonancesignals were detected at 7T. We show that asymmetric NHC ligands, because of their favorable chemistry, can adapt the SABREactive complexes to different chemical scenarios.","lang":"eng"}],"user_id":"100715","_id":"63969","language":[{"iso":"eng"}],"extern":"1","keyword":["dynamic nuclear-polarization","hyperpolarization","enhancement","hydrogen induced polarization","olefin-metathesis catalysts","parahydrogen-induced polarization","peptides","Physics","sabre","spectroscopy"]},{"keyword":["speech enhancement","noise tracking","optimal smoothing"],"language":[{"iso":"eng"}],"_id":"11739","user_id":"44006","department":[{"_id":"54"}],"abstract":[{"lang":"eng","text":"Noise tracking is an important component of speech enhancement algorithms. Of the many noise trackers proposed, Minimum Statistics (MS) is a particularly popular one due to its simple parameterization and at the same time excellent performance. In this paper we propose to further reduce the number of MS parameters by giving an alternative derivation of an optimal smoothing constant. At the same time the noise tracking performance is improved as is demonstrated by experiments employing speech degraded by various noise types and at different SNR values."}],"status":"public","type":"conference","publication":"Interspeech 2015","title":"On Optimal Smoothing in Minimum Statistics Based Noise Tracking","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2015/ChHa15.pdf"}],"date_updated":"2022-01-06T06:51:08Z","oa":"1","author":[{"full_name":"Chinaev, Aleksej","last_name":"Chinaev","first_name":"Aleksej"},{"first_name":"Reinhold","id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach"}],"date_created":"2019-07-12T05:27:19Z","year":"2015","citation":{"chicago":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “On Optimal Smoothing in Minimum Statistics Based Noise Tracking.” In <i>Interspeech 2015</i>, 1785–89, 2015.","ieee":"A. Chinaev and R. Haeb-Umbach, “On Optimal Smoothing in Minimum Statistics Based Noise Tracking,” in <i>Interspeech 2015</i>, 2015, pp. 1785–1789.","ama":"Chinaev A, Haeb-Umbach R. On Optimal Smoothing in Minimum Statistics Based Noise Tracking. In: <i>Interspeech 2015</i>. ; 2015:1785-1789.","apa":"Chinaev, A., &#38; Haeb-Umbach, R. (2015). On Optimal Smoothing in Minimum Statistics Based Noise Tracking. In <i>Interspeech 2015</i> (pp. 1785–1789).","short":"A. Chinaev, R. Haeb-Umbach, in: Interspeech 2015, 2015, pp. 1785–1789.","mla":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “On Optimal Smoothing in Minimum Statistics Based Noise Tracking.” <i>Interspeech 2015</i>, 2015, pp. 1785–89.","bibtex":"@inproceedings{Chinaev_Haeb-Umbach_2015, title={On Optimal Smoothing in Minimum Statistics Based Noise Tracking}, booktitle={Interspeech 2015}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2015}, pages={1785–1789} }"},"page":"1785-1789","related_material":{"link":[{"relation":"supplementary_material","description":"Poster","url":"https://groups.uni-paderborn.de/nt/pubs/2015/ChHa15_Poster.pdf"}]}},{"date_updated":"2022-01-06T06:51:09Z","oa":"1","author":[{"last_name":"Heymann","full_name":"Heymann, Jahn","id":"9168","first_name":"Jahn"},{"first_name":"Reinhold","id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach"},{"last_name":"Golik","full_name":"Golik, P.","first_name":"P."},{"first_name":"R.","last_name":"Schlueter","full_name":"Schlueter, R."}],"date_created":"2019-07-12T05:28:45Z","title":"Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions","doi":"10.1109/ICASSP.2015.7178933","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2015/hey_icassp_2015.pdf"}],"year":"2015","page":"5053-5057","citation":{"apa":"Heymann, J., Haeb-Umbach, R., Golik, P., &#38; Schlueter, R. (2015). Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions. In <i>Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on</i> (pp. 5053–5057). <a href=\"https://doi.org/10.1109/ICASSP.2015.7178933\">https://doi.org/10.1109/ICASSP.2015.7178933</a>","bibtex":"@inproceedings{Heymann_Haeb-Umbach_Golik_Schlueter_2015, title={Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2015.7178933\">10.1109/ICASSP.2015.7178933</a>}, booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on}, author={Heymann, Jahn and Haeb-Umbach, Reinhold and Golik, P. and Schlueter, R.}, year={2015}, pages={5053–5057} }","short":"J. Heymann, R. Haeb-Umbach, P. Golik, R. Schlueter, in: Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On, 2015, pp. 5053–5057.","mla":"Heymann, Jahn, et al. “Unsupervised Adaptation of a Denoising Autoencoder by Bayesian Feature Enhancement for Reverberant Asr under Mismatch Conditions.” <i>Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On</i>, 2015, pp. 5053–57, doi:<a href=\"https://doi.org/10.1109/ICASSP.2015.7178933\">10.1109/ICASSP.2015.7178933</a>.","chicago":"Heymann, Jahn, Reinhold Haeb-Umbach, P. Golik, and R. Schlueter. “Unsupervised Adaptation of a Denoising Autoencoder by Bayesian Feature Enhancement for Reverberant Asr under Mismatch Conditions.” In <i>Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On</i>, 5053–57, 2015. <a href=\"https://doi.org/10.1109/ICASSP.2015.7178933\">https://doi.org/10.1109/ICASSP.2015.7178933</a>.","ieee":"J. Heymann, R. Haeb-Umbach, P. Golik, and R. Schlueter, “Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions,” in <i>Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on</i>, 2015, pp. 5053–5057.","ama":"Heymann J, Haeb-Umbach R, Golik P, Schlueter R. Unsupervised adaptation of a denoising autoencoder by Bayesian Feature Enhancement for reverberant asr under mismatch conditions. In: <i>Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference On</i>. ; 2015:5053-5057. doi:<a href=\"https://doi.org/10.1109/ICASSP.2015.7178933\">10.1109/ICASSP.2015.7178933</a>"},"_id":"11813","department":[{"_id":"54"}],"user_id":"44006","keyword":["codecs","signal denoising","speech recognition","Bayesian feature enhancement","denoising autoencoder","reverberant ASR","single-channel speech recognition","speaker to microphone distances","unsupervised adaptation","Adaptation models","Noise reduction","Reverberation","Speech","Speech recognition","Training","deep neuronal networks","denoising autoencoder","feature enhancement","robust speech recognition"],"language":[{"iso":"eng"}],"publication":"Acoustics, Speech and Signal Processing (ICASSP), 2015 IEEE International Conference on","type":"conference","abstract":[{"lang":"eng","text":"The parametric Bayesian Feature Enhancement (BFE) and a datadriven Denoising Autoencoder (DA) both bring performance gains in severe single-channel speech recognition conditions. The first can be adjusted to different conditions by an appropriate parameter setting, while the latter needs to be trained on conditions similar to the ones expected at decoding time, making it vulnerable to a mismatch between training and test conditions. We use a DNN backend and study reverberant ASR under three types of mismatch conditions: different room reverberation times, different speaker to microphone distances and the difference between artificially reverberated data and the recordings in a reverberant environment. We show that for these mismatch conditions BFE can provide the targets for a DA. This unsupervised adaptation provides a performance gain over the direct use of BFE and even enables to compensate for the mismatch of real and simulated reverberant data."}],"status":"public"},{"user_id":"44006","department":[{"_id":"54"}],"_id":"11862","language":[{"iso":"eng"}],"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"],"type":"journal_article","publication":"IEEE Transactions on Audio, Speech, and Language Processing","status":"public","abstract":[{"lang":"eng","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."}],"date_created":"2019-07-12T05:29:42Z","author":[{"first_name":"Volker","full_name":"Leutnant, Volker","last_name":"Leutnant"},{"first_name":"Alexander","full_name":"Krueger, Alexander","last_name":"Krueger"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"volume":21,"date_updated":"2022-01-06T06:51:11Z","doi":"10.1109/TASL.2013.2258013","title":"Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition","issue":"8","citation":{"apa":"Leutnant, V., Krueger, A., &#38; Haeb-Umbach, R. (2013). Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>21</i>(8), 1640–1652. <a href=\"https://doi.org/10.1109/TASL.2013.2258013\">https://doi.org/10.1109/TASL.2013.2258013</a>","bibtex":"@article{Leutnant_Krueger_Haeb-Umbach_2013, title={Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition}, volume={21}, DOI={<a href=\"https://doi.org/10.1109/TASL.2013.2258013\">10.1109/TASL.2013.2258013</a>}, 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} }","short":"V. Leutnant, A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 21 (2013) 1640–1652.","mla":"Leutnant, Volker, et al. “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 21, no. 8, 2013, pp. 1640–52, doi:<a href=\"https://doi.org/10.1109/TASL.2013.2258013\">10.1109/TASL.2013.2258013</a>.","ama":"Leutnant V, Krueger A, Haeb-Umbach R. Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2013;21(8):1640-1652. doi:<a href=\"https://doi.org/10.1109/TASL.2013.2258013\">10.1109/TASL.2013.2258013</a>","chicago":"Leutnant, Volker, Alexander Krueger, and Reinhold Haeb-Umbach. “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 21, no. 8 (2013): 1640–52. <a href=\"https://doi.org/10.1109/TASL.2013.2258013\">https://doi.org/10.1109/TASL.2013.2258013</a>.","ieee":"V. Leutnant, A. Krueger, and R. Haeb-Umbach, “Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 21, no. 8, pp. 1640–1652, 2013."},"intvolume":"        21","page":"1640-1652","year":"2013"},{"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12.pdf","open_access":"1"}],"title":"Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor","author":[{"first_name":"Aleksej","last_name":"Chinaev","full_name":"Chinaev, Aleksej"},{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"full_name":"Tran Vu, Dang Hai","last_name":"Tran Vu","first_name":"Dang Hai"},{"full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"date_created":"2019-07-12T05:27:26Z","oa":"1","date_updated":"2022-01-06T06:51:08Z","citation":{"chicago":"Chinaev, Aleksej, Alexander Krueger, Dang Hai Tran Vu, and Reinhold Haeb-Umbach. “Improved Noise Power Spectral Density Tracking by a MAP-Based Postprocessor.” In <i>37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>, 2012.","ieee":"A. Chinaev, A. Krueger, D. H. Tran Vu, and R. Haeb-Umbach, “Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor,” in <i>37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>, 2012.","ama":"Chinaev A, Krueger A, Tran Vu DH, Haeb-Umbach R. Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In: <i>37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>. ; 2012.","apa":"Chinaev, A., Krueger, A., Tran Vu, D. H., &#38; Haeb-Umbach, R. (2012). Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor. In <i>37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>.","short":"A. Chinaev, A. Krueger, D.H. Tran Vu, R. Haeb-Umbach, in: 37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012), 2012.","mla":"Chinaev, Aleksej, et al. “Improved Noise Power Spectral Density Tracking by a MAP-Based Postprocessor.” <i>37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)</i>, 2012.","bibtex":"@inproceedings{Chinaev_Krueger_Tran Vu_Haeb-Umbach_2012, title={Improved Noise Power Spectral Density Tracking by a MAP-based Postprocessor}, booktitle={37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)}, author={Chinaev, Aleksej and Krueger, Alexander and Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2012} }"},"year":"2012","related_material":{"link":[{"relation":"supplementary_material","description":"Presentation","url":"https://groups.uni-paderborn.de/nt/pubs/2012/ChKrDaHa12_Talk.pdf"}]},"language":[{"iso":"eng"}],"keyword":["MAP parameter estimation","noise power estimation","speech enhancement"],"user_id":"44006","department":[{"_id":"54"}],"_id":"11745","status":"public","abstract":[{"lang":"eng","text":"In this paper we present a novel noise power spectral density tracking algorithm and its use in single-channel speech enhancement. It has the unique feature that it is able to track the noise statistics even if speech is dominant in a given time-frequency bin. As a consequence it can follow non-stationary noise superposed by speech, even in the critical case of rising noise power. The algorithm requires an initial estimate of the power spectrum of speech and is thus meant to be used as a postprocessor to a first speech enhancement stage. An experimental comparison with a state-of-the-art noise tracking algorithm demonstrates lower estimation errors under low SNR conditions and smaller fluctuations of the estimated values, resulting in improved speech quality as measured by PESQ scores."}],"type":"conference","publication":"37th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2012)"},{"language":[{"iso":"eng"}],"keyword":["Robust Automatic Speech Recognition","Bayesian feature enhancement","observation model for reverberant and noisy speech"],"user_id":"44006","department":[{"_id":"54"}],"_id":"11864","status":"public","abstract":[{"lang":"eng","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."}],"type":"conference","publication":"Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on","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","date_created":"2019-07-12T05:29:44Z","author":[{"full_name":"Leutnant, Volker","last_name":"Leutnant","first_name":"Volker"},{"first_name":"Alexander","full_name":"Krueger, Alexander","last_name":"Krueger"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold"}],"oa":"1","date_updated":"2022-01-06T06:51:11Z","citation":{"ama":"Leutnant V, Krueger A, Haeb-Umbach R. A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR. In: <i>Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On</i>. ; 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 <i>Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On</i>, 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 <i>Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on</i>, 2012.","apa":"Leutnant, V., Krueger, A., &#38; Haeb-Umbach, R. (2012). A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR. In <i>Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on</i>.","short":"V. Leutnant, A. Krueger, R. Haeb-Umbach, in: Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On, 2012.","mla":"Leutnant, Volker, et al. “A Statistical Observation Model For Noisy Reverberant Speech Features and Its Application to Robust ASR.” <i>Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference On</i>, 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} }"},"year":"2012"},{"user_id":"42165","department":[{"_id":"424"}],"_id":"6081","language":[{"iso":"eng"}],"funded_apc":"1","keyword":["attentional blink","attentional enhancement","lag-1 sparing","prior entry","temporal cueing","visual attention","rapid serial presentation","Adolescent","Adult","Attention","Attentional Blink","Color Perception","Cues","Female","Humans","Male","Neuropsychological Tests","Pattern Recognition","Visual","Time Factors","Visual Perception","Young Adult","Cues","Serial Recall","Visual Attention","Eyeblink Reflex"],"type":"journal_article","publication":"Journal of Experimental Psychology: Human Perception and Performance","status":"public","abstract":[{"text":"The law of prior entry states that attended objects come to consciousness more quickly than unattended ones. This has been well established in spatial cueing paradigms, where two task-relevant stimuli are presented near-simultaneously at two different locations. Here, we suggest that prior entry also plays a pivotal role in temporal attention paradigms, where stimuli appear at the same location but at distinct moments in time, in rapid serial presentation (RSVP). Specifically, we hypothesize that prior entry can explain temporal order reversals in reporting two targets from RSVP. In support of this, three experiments show that cueing attention toward either of the targets has a strong influence on order errors. We conclude that prior entry provides a viable explanation of the way in which relevant information is prioritized in RSVP. (PsycINFO Database Record (c) 2016 APA, all rights reserved)","lang":"eng"}],"date_created":"2018-12-10T07:06:20Z","author":[{"first_name":"Frederic","last_name":"Hilkenmeier","full_name":"Hilkenmeier, Frederic"},{"first_name":"Christian N. L.","last_name":"Olivers","full_name":"Olivers, Christian N. L."},{"first_name":"Ingrid","id":"451","full_name":"Scharlau, Ingrid","last_name":"Scharlau","orcid":"0000-0003-2364-9489"}],"volume":38,"date_updated":"2022-06-06T16:35:40Z","title":"Prior entry and temporal attention: Cueing affects order errors in RSVP.","issue":"1","publication_status":"published","publication_identifier":{"issn":["0096-1523"]},"citation":{"bibtex":"@article{Hilkenmeier_Olivers_Scharlau_2012, title={Prior entry and temporal attention: Cueing affects order errors in RSVP.}, volume={38}, number={1}, journal={Journal of Experimental Psychology: Human Perception and Performance}, author={Hilkenmeier, Frederic and Olivers, Christian N. L. and Scharlau, Ingrid}, year={2012}, pages={180–190} }","short":"F. Hilkenmeier, C.N.L. Olivers, I. Scharlau, Journal of Experimental Psychology: Human Perception and Performance 38 (2012) 180–190.","mla":"Hilkenmeier, Frederic, et al. “Prior Entry and Temporal Attention: Cueing Affects Order Errors in RSVP.” <i>Journal of Experimental Psychology: Human Perception and Performance</i>, vol. 38, no. 1, 2012, pp. 180–90.","ama":"Hilkenmeier F, Olivers CNL, Scharlau I. Prior entry and temporal attention: Cueing affects order errors in RSVP. <i>Journal of Experimental Psychology: Human Perception and Performance</i>. 2012;38(1):180-190.","apa":"Hilkenmeier, F., Olivers, C. N. L., &#38; Scharlau, I. (2012). Prior entry and temporal attention: Cueing affects order errors in RSVP. <i>Journal of Experimental Psychology: Human Perception and Performance</i>, <i>38</i>(1), 180–190.","ieee":"F. Hilkenmeier, C. N. L. Olivers, and I. Scharlau, “Prior entry and temporal attention: Cueing affects order errors in RSVP.,” <i>Journal of Experimental Psychology: Human Perception and Performance</i>, vol. 38, no. 1, pp. 180–190, 2012.","chicago":"Hilkenmeier, Frederic, Christian N. L. Olivers, and Ingrid Scharlau. “Prior Entry and Temporal Attention: Cueing Affects Order Errors in RSVP.” <i>Journal of Experimental Psychology: Human Perception and Performance</i> 38, no. 1 (2012): 180–90."},"intvolume":"        38","page":"180 - 190","year":"2012"},{"publication":"IEEE Transactions on Audio, Speech, and Language Processing","abstract":[{"lang":"eng","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."}],"language":[{"iso":"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"],"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","type":"journal_article","status":"public","user_id":"44006","department":[{"_id":"54"}],"_id":"11850","citation":{"mla":"Krueger, Alexander, et al. “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 19, no. 1, 2011, pp. 206–19, doi:<a href=\"https://doi.org/10.1109/TASL.2010.2047324\">10.1109/TASL.2010.2047324</a>.","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={<a href=\"https://doi.org/10.1109/TASL.2010.2047324\">10.1109/TASL.2010.2047324</a>}, 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.","apa":"Krueger, A., Warsitz, E., &#38; Haeb-Umbach, R. (2011). Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>19</i>(1), 206–219. <a href=\"https://doi.org/10.1109/TASL.2010.2047324\">https://doi.org/10.1109/TASL.2010.2047324</a>","ama":"Krueger A, Warsitz E, Haeb-Umbach R. Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2011;19(1):206-219. doi:<a href=\"https://doi.org/10.1109/TASL.2010.2047324\">10.1109/TASL.2010.2047324</a>","ieee":"A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 19, no. 1, pp. 206–219, 2011.","chicago":"Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Speech Enhancement With a GSC-Like Structure Employing Eigenvector-Based Transfer Function Ratios Estimation.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 19, no. 1 (2011): 206–19. <a href=\"https://doi.org/10.1109/TASL.2010.2047324\">https://doi.org/10.1109/TASL.2010.2047324</a>."},"page":"206-219","intvolume":"        19","author":[{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"first_name":"Ernst","last_name":"Warsitz","full_name":"Warsitz, Ernst"},{"last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242","first_name":"Reinhold"}],"volume":19,"date_updated":"2022-01-06T06:51:11Z","oa":"1","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2011/KrWaHa11.pdf","open_access":"1"}],"doi":"10.1109/TASL.2010.2047324"},{"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":{"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>","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>.","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>","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>.","short":"A. Krueger, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 18 (2010) 1692–1707.","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} }"},"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":[{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold"}]},{"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"],"language":[{"iso":"eng"}],"_id":"11913","user_id":"44006","department":[{"_id":"54"}],"abstract":[{"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.","lang":"eng"}],"status":"public","type":"conference","publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)","title":"Blind speech separation employing directional statistics in an Expectation Maximization framework","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2010/DaHa10-2.pdf"}],"doi":"10.1109/ICASSP.2010.5495994","oa":"1","date_updated":"2022-01-06T06:51:12Z","author":[{"first_name":"Dang Hai","full_name":"Tran Vu, Dang Hai","last_name":"Tran Vu"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"date_created":"2019-07-12T05:30:40Z","year":"2010","citation":{"apa":"Tran Vu, D. H., &#38; Haeb-Umbach, R. (2010). Blind speech separation employing directional statistics in an Expectation Maximization framework. In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i> (pp. 241–244). <a href=\"https://doi.org/10.1109/ICASSP.2010.5495994\">https://doi.org/10.1109/ICASSP.2010.5495994</a>","bibtex":"@inproceedings{Tran Vu_Haeb-Umbach_2010, title={Blind speech separation employing directional statistics in an Expectation Maximization framework}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2010.5495994\">10.1109/ICASSP.2010.5495994</a>}, 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} }","mla":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Employing Directional Statistics in an Expectation Maximization Framework.” <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 2010, pp. 241–44, doi:<a href=\"https://doi.org/10.1109/ICASSP.2010.5495994\">10.1109/ICASSP.2010.5495994</a>.","short":"D.H. Tran Vu, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010), 2010, pp. 241–244.","ama":"Tran Vu DH, Haeb-Umbach R. Blind speech separation employing directional statistics in an Expectation Maximization framework. In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>. ; 2010:241-244. doi:<a href=\"https://doi.org/10.1109/ICASSP.2010.5495994\">10.1109/ICASSP.2010.5495994</a>","ieee":"D. H. Tran Vu and R. Haeb-Umbach, “Blind speech separation employing directional statistics in an Expectation Maximization framework,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 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 <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2010)</i>, 241–44, 2010. <a href=\"https://doi.org/10.1109/ICASSP.2010.5495994\">https://doi.org/10.1109/ICASSP.2010.5495994</a>."},"page":"241-244"},{"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"],"language":[{"iso":"eng"}],"publication":"IEEE Transactions on Audio, Speech, and Language Processing","abstract":[{"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.","lang":"eng"}],"date_created":"2019-07-12T05:31:08Z","title":"Approaches to Iterative Speech Feature Enhancement and Recognition","issue":"5","year":"2009","_id":"11937","department":[{"_id":"54"}],"user_id":"44006","type":"journal_article","status":"public","date_updated":"2022-01-06T06:51:12Z","oa":"1","volume":17,"author":[{"first_name":"Stefan","full_name":"Windmann, Stefan","last_name":"Windmann"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"doi":"10.1109/TASL.2009.2014894","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2009/WiHa09-1.pdf"}],"page":"974-984","intvolume":"        17","citation":{"apa":"Windmann, S., &#38; Haeb-Umbach, R. (2009). Approaches to Iterative Speech Feature Enhancement and Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>17</i>(5), 974–984. <a href=\"https://doi.org/10.1109/TASL.2009.2014894\">https://doi.org/10.1109/TASL.2009.2014894</a>","mla":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech Feature Enhancement and Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 17, no. 5, 2009, pp. 974–84, doi:<a href=\"https://doi.org/10.1109/TASL.2009.2014894\">10.1109/TASL.2009.2014894</a>.","short":"S. Windmann, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 17 (2009) 974–984.","bibtex":"@article{Windmann_Haeb-Umbach_2009, title={Approaches to Iterative Speech Feature Enhancement and Recognition}, volume={17}, DOI={<a href=\"https://doi.org/10.1109/TASL.2009.2014894\">10.1109/TASL.2009.2014894</a>}, number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2009}, pages={974–984} }","ama":"Windmann S, Haeb-Umbach R. Approaches to Iterative Speech Feature Enhancement and Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2009;17(5):974-984. doi:<a href=\"https://doi.org/10.1109/TASL.2009.2014894\">10.1109/TASL.2009.2014894</a>","ieee":"S. Windmann and R. Haeb-Umbach, “Approaches to Iterative Speech Feature Enhancement and Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 17, no. 5, pp. 974–984, 2009.","chicago":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Approaches to Iterative Speech Feature Enhancement and Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 17, no. 5 (2009): 974–84. <a href=\"https://doi.org/10.1109/TASL.2009.2014894\">https://doi.org/10.1109/TASL.2009.2014894</a>."}},{"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"],"language":[{"iso":"eng"}],"_id":"11935","department":[{"_id":"54"}],"user_id":"44006","abstract":[{"lang":"eng","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."}],"status":"public","publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)","type":"conference","title":"Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller","doi":"10.1109/ICASSP.2008.4517549","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/WaKrHa08.pdf"}],"oa":"1","date_updated":"2022-01-06T06:51:12Z","date_created":"2019-07-12T05:31:06Z","author":[{"last_name":"Warsitz","full_name":"Warsitz, Ernst","first_name":"Ernst"},{"last_name":"Krueger","full_name":"Krueger, Alexander","first_name":"Alexander"},{"last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"year":"2008","page":"73-76","citation":{"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>","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>.","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.","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>.","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} }","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>"}},{"oa":"1","date_updated":"2022-01-06T06:51:12Z","author":[{"full_name":"Windmann, Stefan","last_name":"Windmann","first_name":"Stefan"},{"last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242","first_name":"Reinhold"}],"date_created":"2019-07-12T05:31:11Z","title":"Modeling the dynamics of speech and noise for speech feature enhancement in ASR","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/WiHa08-1.pdf"}],"doi":"10.1109/ICASSP.2008.4518633","year":"2008","citation":{"short":"S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–4412.","bibtex":"@inproceedings{Windmann_Haeb-Umbach_2008, title={Modeling the dynamics of speech and noise for speech feature enhancement in ASR}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2008.4518633\">10.1109/ICASSP.2008.4518633</a>}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2008}, pages={4409–4412} }","mla":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Modeling the Dynamics of Speech and Noise for Speech Feature Enhancement in ASR.” <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 2008, pp. 4409–12, doi:<a href=\"https://doi.org/10.1109/ICASSP.2008.4518633\">10.1109/ICASSP.2008.4518633</a>.","apa":"Windmann, S., &#38; Haeb-Umbach, R. (2008). Modeling the dynamics of speech and noise for speech feature enhancement in ASR. In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i> (pp. 4409–4412). <a href=\"https://doi.org/10.1109/ICASSP.2008.4518633\">https://doi.org/10.1109/ICASSP.2008.4518633</a>","chicago":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Modeling the Dynamics of Speech and Noise for Speech Feature Enhancement in ASR.” In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 4409–12, 2008. <a href=\"https://doi.org/10.1109/ICASSP.2008.4518633\">https://doi.org/10.1109/ICASSP.2008.4518633</a>.","ieee":"S. Windmann and R. Haeb-Umbach, “Modeling the dynamics of speech and noise for speech feature enhancement in ASR,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 2008, pp. 4409–4412.","ama":"Windmann S, Haeb-Umbach R. Modeling the dynamics of speech and noise for speech feature enhancement in ASR. In: <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>. ; 2008:4409-4412. doi:<a href=\"https://doi.org/10.1109/ICASSP.2008.4518633\">10.1109/ICASSP.2008.4518633</a>"},"page":"4409-4412","_id":"11939","user_id":"44006","department":[{"_id":"54"}],"keyword":["a posteriori probability","AURORA2 database","Bayesian inference","Bayes methods","channel bank filters","extended Kalman filter banks","hidden noise state variable","Kalman filters","noise dynamics","speech enhancement","speech feature enhancement","speech feature trajectory","switching linear dynamical model approach"],"language":[{"iso":"eng"}],"type":"conference","publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)","abstract":[{"text":"In this paper a switching linear dynamical model (SLDM) approach for speech feature enhancement is improved by employing more accurate models for the dynamics of speech and noise. The model of the clean speech feature trajectory is improved by augmenting the state vector to capture information derived from the delta features. Further a hidden noise state variable is introduced to obtain a more elaborated model for the noise dynamics. Approximate Bayesian inference in the SLDM is carried out by a bank of extended Kalman filters, whose outputs are combined according to the a posteriori probability of the individual state models. Experimental results on the AURORA2 database show improved recognition accuracy.","lang":"eng"}],"status":"public"},{"title":"Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2006/WiHa06-2.pdf","open_access":"1"}],"doi":"10.1109/ICASSP.2006.1660058","oa":"1","date_updated":"2022-01-06T06:51:12Z","date_created":"2019-07-12T05:31:15Z","author":[{"first_name":"Stefan","full_name":"Windmann, Stefan","last_name":"Windmann"},{"last_name":"Haeb-Umbach","id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold"}],"volume":1,"year":"2006","citation":{"mla":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Iterative Speech Enhancement Using a Non-Linear Dynamic State Model of Speech and Its Parameters.” <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.2006.1660058\">10.1109/ICASSP.2006.1660058</a>.","bibtex":"@inproceedings{Windmann_Haeb-Umbach_2006, title={Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters}, volume={1}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2006.1660058\">10.1109/ICASSP.2006.1660058</a>}, booktitle={IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}, author={Windmann, Stefan and Haeb-Umbach, Reinhold}, year={2006}, pages={I} }","short":"S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006), 2006, p. I.","apa":"Windmann, S., &#38; Haeb-Umbach, R. (2006). Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters. 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.2006.1660058\">https://doi.org/10.1109/ICASSP.2006.1660058</a>","ama":"Windmann S, Haeb-Umbach R. Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters. 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.2006.1660058\">10.1109/ICASSP.2006.1660058</a>","ieee":"S. Windmann and R. Haeb-Umbach, “Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters,” in <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)</i>, 2006, vol. 1, p. I.","chicago":"Windmann, Stefan, and Reinhold Haeb-Umbach. “Iterative Speech Enhancement Using a Non-Linear Dynamic State Model of Speech and Its Parameters.” 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.2006.1660058\">https://doi.org/10.1109/ICASSP.2006.1660058</a>."},"intvolume":"         1","page":"I","keyword":["clean speech training data","iterative methods","iterative speech enhancement","Kalman filter","Kalman filters","Kalman-LM-iterative algorithm","line spectral pair parameters","log-spectral distance","marginalized particle filter","noise level","nonlinear dynamic state speech model","particle filtering (numerical methods)","single channel speech enhancement","SNR gains","speech enhancement","speech samples"],"language":[{"iso":"eng"}],"_id":"11943","user_id":"44006","department":[{"_id":"54"}],"abstract":[{"text":"A marginalized particle filter is proposed for performing single channel speech enhancement with a non-linear dynamic state model. The system consists of a particle filter for tracking line spectral pair (LSP) parameters and a Kalman filter per particle for speech enhancement. The state model for the LSPs has been learnt on clean speech training data. In our approach parameters and speech samples are processed at different time scales by assuming the parameters to be constant for small blocks of data. Further enhancement is obtained by an iteration which can be applied on these small blocks. The experiments show that similar SNR gains are obtained as with the Kalman-LM-iterative algorithm. However better values of the noise level and the log-spectral distance are achieved","lang":"eng"}],"status":"public","type":"conference","publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)"},{"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"}],"status":"public","publication":"IEEE Workshop on Multimedia Signal Processing (MMSP 2004)","type":"conference","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"],"language":[{"iso":"eng"}],"_id":"11931","department":[{"_id":"54"}],"user_id":"44006","year":"2004","page":"367-370","citation":{"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>","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>.","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} }","short":"E. Warsitz, R. Haeb-Umbach, in: IEEE Workshop on Multimedia Signal Processing (MMSP 2004), 2004, pp. 367–370.","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>","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>.","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."},"title":"Robust speaker direction estimation with particle filtering","doi":"10.1109/MMSP.2004.1436569","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2004/WaHa04.pdf","open_access":"1"}],"date_updated":"2022-01-06T06:51:12Z","oa":"1","author":[{"first_name":"Ernst","last_name":"Warsitz","full_name":"Warsitz, Ernst"},{"first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242","last_name":"Haeb-Umbach"}],"date_created":"2019-07-12T05:31:01Z"}]