[{"user_id":"3118","_id":"10741","publisher":"Paderborn University","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:50:50Z","author":[{"last_name":"Sprenger","first_name":"Alexander","full_name":"Sprenger, Alexander"}],"status":"public","year":"2013","title":"MiBenchHybrid : Erweiterung eines Benchmarks um Hardwarebeschleunigung","department":[{"_id":"78"}],"type":"bachelorsthesis","date_created":"2019-07-10T11:59:40Z","supervisor":[{"full_name":"Meisner, Sebastian","last_name":"Meisner","first_name":"Sebastian"}],"citation":{"bibtex":"@book{Sprenger_2013, title={MiBenchHybrid : Erweiterung eines Benchmarks um Hardwarebeschleunigung}, publisher={Paderborn University}, author={Sprenger, Alexander}, year={2013} }","ama":"Sprenger A. <i>MiBenchHybrid : Erweiterung Eines Benchmarks Um Hardwarebeschleunigung</i>. Paderborn University; 2013.","mla":"Sprenger, Alexander. <i>MiBenchHybrid : Erweiterung Eines Benchmarks Um Hardwarebeschleunigung</i>. Paderborn University, 2013.","chicago":"Sprenger, Alexander. <i>MiBenchHybrid : Erweiterung Eines Benchmarks Um Hardwarebeschleunigung</i>. Paderborn University, 2013.","short":"A. Sprenger, MiBenchHybrid : Erweiterung Eines Benchmarks Um Hardwarebeschleunigung, Paderborn University, 2013.","ieee":"A. Sprenger, <i>MiBenchHybrid : Erweiterung eines Benchmarks um Hardwarebeschleunigung</i>. Paderborn University, 2013.","apa":"Sprenger, A. (2013). <i>MiBenchHybrid : Erweiterung eines Benchmarks um Hardwarebeschleunigung</i>. Paderborn University."}},{"language":[{"iso":"eng"}],"_id":"10743","publisher":"Paderborn University","user_id":"3118","author":[{"first_name":"Philipp","last_name":"Steppeler","full_name":"Steppeler, Philipp"}],"year":"2013","title":"Beschleunigung von Einzelbild-Erkennungsverfahren auf Datenfluss basierenden HPC Systemen","status":"public","date_updated":"2022-01-06T06:50:50Z","date_created":"2019-07-10T12:00:44Z","department":[{"_id":"78"}],"type":"bachelorsthesis","citation":{"short":"P. Steppeler, Beschleunigung von Einzelbild-Erkennungsverfahren Auf Datenfluss Basierenden HPC Systemen, Paderborn University, 2013.","chicago":"Steppeler, Philipp. <i>Beschleunigung von Einzelbild-Erkennungsverfahren Auf Datenfluss Basierenden HPC Systemen</i>. Paderborn University, 2013.","ieee":"P. Steppeler, <i>Beschleunigung von Einzelbild-Erkennungsverfahren auf Datenfluss basierenden HPC Systemen</i>. Paderborn University, 2013.","apa":"Steppeler, P. (2013). <i>Beschleunigung von Einzelbild-Erkennungsverfahren auf Datenfluss basierenden HPC Systemen</i>. Paderborn University.","bibtex":"@book{Steppeler_2013, title={Beschleunigung von Einzelbild-Erkennungsverfahren auf Datenfluss basierenden HPC Systemen}, publisher={Paderborn University}, author={Steppeler, Philipp}, year={2013} }","ama":"Steppeler P. <i>Beschleunigung von Einzelbild-Erkennungsverfahren Auf Datenfluss Basierenden HPC Systemen</i>. Paderborn University; 2013.","mla":"Steppeler, Philipp. <i>Beschleunigung von Einzelbild-Erkennungsverfahren Auf Datenfluss Basierenden HPC Systemen</i>. Paderborn University, 2013."}},{"type":"conference","department":[{"_id":"78"}],"date_created":"2019-07-10T12:01:51Z","publication":"Real-Time Conference","citation":{"apa":"Toebermann, C., Geibel, D., Hau, M., Brandl, R., Kaufmann, P., Ma, C., … Degner, T. (2013). Real-Time Simulation of Distribution Grids with high Penetration of Regenerative and Distributed Generation. In <i>Real-Time Conference</i>. OPAL RT Paris.","ieee":"C. Toebermann <i>et al.</i>, “Real-Time Simulation of Distribution Grids with high Penetration of Regenerative and Distributed Generation,” in <i>Real-Time Conference</i>, 2013.","chicago":"Toebermann, Christian, Daniel Geibel, Manuel Hau, Ron Brandl, Paul Kaufmann, Chenjie Ma, Martin Braun, and Tobias Degner. “Real-Time Simulation of Distribution Grids with High Penetration of Regenerative and Distributed Generation.” In <i>Real-Time Conference</i>. OPAL RT Paris, 2013.","short":"C. Toebermann, D. Geibel, M. Hau, R. Brandl, P. Kaufmann, C. Ma, M. Braun, T. Degner, in: Real-Time Conference, OPAL RT Paris, 2013.","mla":"Toebermann, Christian, et al. “Real-Time Simulation of Distribution Grids with High Penetration of Regenerative and Distributed Generation.” <i>Real-Time Conference</i>, OPAL RT Paris, 2013.","ama":"Toebermann C, Geibel D, Hau M, et al. Real-Time Simulation of Distribution Grids with high Penetration of Regenerative and Distributed Generation. In: <i>Real-Time Conference</i>. OPAL RT Paris; 2013.","bibtex":"@inproceedings{Toebermann_Geibel_Hau_Brandl_Kaufmann_Ma_Braun_Degner_2013, title={Real-Time Simulation of Distribution Grids with high Penetration of Regenerative and Distributed Generation}, booktitle={Real-Time Conference}, publisher={OPAL RT Paris}, author={Toebermann, Christian and Geibel, Daniel and Hau, Manuel and Brandl, Ron and Kaufmann, Paul and Ma, Chenjie and Braun, Martin and Degner, Tobias}, year={2013} }"},"user_id":"3118","publisher":"OPAL RT Paris","_id":"10745","date_updated":"2022-01-06T06:50:50Z","status":"public","year":"2013","title":"Real-Time Simulation of Distribution Grids with high Penetration of Regenerative and Distributed Generation","author":[{"last_name":"Toebermann","first_name":"Christian","full_name":"Toebermann, Christian"},{"full_name":"Geibel, Daniel","last_name":"Geibel","first_name":"Daniel"},{"last_name":"Hau","first_name":"Manuel","full_name":"Hau, Manuel"},{"full_name":"Brandl, Ron","last_name":"Brandl","first_name":"Ron"},{"full_name":"Kaufmann, Paul","first_name":"Paul","last_name":"Kaufmann"},{"full_name":"Ma, Chenjie","last_name":"Ma","first_name":"Chenjie"},{"full_name":"Braun, Martin","first_name":"Martin","last_name":"Braun"},{"full_name":"Degner, Tobias","last_name":"Degner","first_name":"Tobias"}]},{"date_updated":"2022-01-06T06:50:50Z","author":[{"id":"61186","full_name":"Ghasemzadeh Mohammadi, Hassan","first_name":"Hassan","last_name":"Ghasemzadeh Mohammadi"},{"full_name":"Gaillardon, Pierre-Emmanuel","first_name":"Pierre-Emmanuel","last_name":"Gaillardon"},{"full_name":"Yazdani, Majid","first_name":"Majid","last_name":"Yazdani"},{"first_name":"Giovanni","last_name":"De Micheli","full_name":"De Micheli, Giovanni"}],"status":"public","year":"2013","title":"A fast TCAD-based methodology for Variation analysis of emerging nano-devices","doi":"10.1109/DFT.2013.6653587","user_id":"3118","publisher":"IEEE","_id":"10774","language":[{"iso":"eng"}],"page":"83-88","extern":"1","citation":{"mla":"Ghasemzadeh Mohammadi, Hassan, et al. “A Fast TCAD-Based Methodology for Variation Analysis of Emerging Nano-Devices.” <i>2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)</i>, IEEE, 2013, pp. 83–88, doi:<a href=\"https://doi.org/10.1109/DFT.2013.6653587\">10.1109/DFT.2013.6653587</a>.","ama":"Ghasemzadeh Mohammadi H, Gaillardon P-E, Yazdani M, De Micheli G. A fast TCAD-based methodology for Variation analysis of emerging nano-devices. In: <i>2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)</i>. IEEE; 2013:83-88. doi:<a href=\"https://doi.org/10.1109/DFT.2013.6653587\">10.1109/DFT.2013.6653587</a>","bibtex":"@inproceedings{Ghasemzadeh Mohammadi_Gaillardon_Yazdani_De Micheli_2013, title={A fast TCAD-based methodology for Variation analysis of emerging nano-devices}, DOI={<a href=\"https://doi.org/10.1109/DFT.2013.6653587\">10.1109/DFT.2013.6653587</a>}, booktitle={2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)}, publisher={IEEE}, author={Ghasemzadeh Mohammadi, Hassan and Gaillardon, Pierre-Emmanuel and Yazdani, Majid and De Micheli, Giovanni}, year={2013}, pages={83–88} }","apa":"Ghasemzadeh Mohammadi, H., Gaillardon, P.-E., Yazdani, M., &#38; De Micheli, G. (2013). A fast TCAD-based methodology for Variation analysis of emerging nano-devices. In <i>2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)</i> (pp. 83–88). IEEE. <a href=\"https://doi.org/10.1109/DFT.2013.6653587\">https://doi.org/10.1109/DFT.2013.6653587</a>","ieee":"H. Ghasemzadeh Mohammadi, P.-E. Gaillardon, M. Yazdani, and G. De Micheli, “A fast TCAD-based methodology for Variation analysis of emerging nano-devices,” in <i>2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)</i>, 2013, pp. 83–88.","chicago":"Ghasemzadeh Mohammadi, Hassan, Pierre-Emmanuel Gaillardon, Majid Yazdani, and Giovanni De Micheli. “A Fast TCAD-Based Methodology for Variation Analysis of Emerging Nano-Devices.” In <i>2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)</i>, 83–88. IEEE, 2013. <a href=\"https://doi.org/10.1109/DFT.2013.6653587\">https://doi.org/10.1109/DFT.2013.6653587</a>.","short":"H. Ghasemzadeh Mohammadi, P.-E. Gaillardon, M. Yazdani, G. De Micheli, in: 2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS), IEEE, 2013, pp. 83–88."},"publication":"2013 IEEE International Symposium on Defect and Fault Tolerance in VLSI and Nanotechnology Systems (DFTS)","department":[{"_id":"78"}],"type":"conference","date_created":"2019-07-10T12:10:17Z"},{"author":[{"full_name":"Gaillardon, Pierre-Emmanuel","first_name":"Pierre-Emmanuel","last_name":"Gaillardon"},{"full_name":"Ghasemzadeh Mohammadi, Hassan","first_name":"Hassan","last_name":"Ghasemzadeh Mohammadi","id":"61186"},{"full_name":"De Micheli, Giovanni","last_name":"De Micheli","first_name":"Giovanni"}],"title":"Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study","status":"public","year":"2013","date_updated":"2022-01-06T06:50:50Z","publisher":"IEEE","_id":"10775","language":[{"iso":"eng"}],"page":"1-6","doi":"10.1109/LATW.2013.6562673","user_id":"3118","citation":{"short":"P.-E. Gaillardon, H. Ghasemzadeh Mohammadi, G. De Micheli, in: 2013 14th Latin American Test Workshop-LATW, IEEE, 2013, pp. 1–6.","chicago":"Gaillardon, Pierre-Emmanuel, Hassan Ghasemzadeh Mohammadi, and Giovanni De Micheli. “Vertically-Stacked Silicon Nanowire Transistors with Controllable Polarity: A Robustness Study.” In <i>2013 14th Latin American Test Workshop-LATW</i>, 1–6. IEEE, 2013. <a href=\"https://doi.org/10.1109/LATW.2013.6562673\">https://doi.org/10.1109/LATW.2013.6562673</a>.","apa":"Gaillardon, P.-E., Ghasemzadeh Mohammadi, H., &#38; De Micheli, G. (2013). Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study. In <i>2013 14th Latin American Test Workshop-LATW</i> (pp. 1–6). IEEE. <a href=\"https://doi.org/10.1109/LATW.2013.6562673\">https://doi.org/10.1109/LATW.2013.6562673</a>","ieee":"P.-E. Gaillardon, H. Ghasemzadeh Mohammadi, and G. De Micheli, “Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study,” in <i>2013 14th Latin American Test Workshop-LATW</i>, 2013, pp. 1–6.","ama":"Gaillardon P-E, Ghasemzadeh Mohammadi H, De Micheli G. Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study. In: <i>2013 14th Latin American Test Workshop-LATW</i>. IEEE; 2013:1-6. doi:<a href=\"https://doi.org/10.1109/LATW.2013.6562673\">10.1109/LATW.2013.6562673</a>","bibtex":"@inproceedings{Gaillardon_Ghasemzadeh Mohammadi_De Micheli_2013, title={Vertically-stacked silicon nanowire transistors with controllable polarity: A robustness study}, DOI={<a href=\"https://doi.org/10.1109/LATW.2013.6562673\">10.1109/LATW.2013.6562673</a>}, booktitle={2013 14th Latin American Test Workshop-LATW}, publisher={IEEE}, author={Gaillardon, Pierre-Emmanuel and Ghasemzadeh Mohammadi, Hassan and De Micheli, Giovanni}, year={2013}, pages={1–6} }","mla":"Gaillardon, Pierre-Emmanuel, et al. “Vertically-Stacked Silicon Nanowire Transistors with Controllable Polarity: A Robustness Study.” <i>2013 14th Latin American Test Workshop-LATW</i>, IEEE, 2013, pp. 1–6, doi:<a href=\"https://doi.org/10.1109/LATW.2013.6562673\">10.1109/LATW.2013.6562673</a>."},"publication":"2013 14th Latin American Test Workshop-LATW","extern":"1","date_created":"2019-07-10T12:10:18Z","department":[{"_id":"78"}],"type":"conference"},{"status":"public","title":"Schema-based Parallel Compression and Decompression of XML Data","year":"2013","author":[{"full_name":"Böttcher, Stefan","last_name":"Böttcher","first_name":"Stefan","id":"624"},{"orcid":"0000-0003-1348-6516","last_name":"Feldotto","first_name":"Matthias","full_name":"Feldotto, Matthias","id":"14052"},{"id":"14961","full_name":"Hartel, Rita","last_name":"Hartel","first_name":"Rita"}],"date_updated":"2022-01-06T06:50:53Z","has_accepted_license":"1","page":"77-86","_id":"1093","language":[{"iso":"eng"}],"user_id":"14052","ddc":["000"],"doi":"10.5220/0004366300770086","file_date_updated":"2018-10-31T17:00:33Z","publication":"WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013","citation":{"chicago":"Böttcher, Stefan, Matthias Feldotto, and Rita Hartel. “Schema-Based Parallel Compression and Decompression of XML Data.” In <i>WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013</i>, 77–86, 2013. <a href=\"https://doi.org/10.5220/0004366300770086\">https://doi.org/10.5220/0004366300770086</a>.","short":"S. Böttcher, M. Feldotto, R. Hartel, in: WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013, 2013, pp. 77–86.","ieee":"S. Böttcher, M. Feldotto, and R. Hartel, “Schema-based Parallel Compression and Decompression of XML Data,” in <i>WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013</i>, 2013, pp. 77–86.","apa":"Böttcher, S., Feldotto, M., &#38; Hartel, R. (2013). Schema-based Parallel Compression and Decompression of XML Data. In <i>WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013</i> (pp. 77–86). <a href=\"https://doi.org/10.5220/0004366300770086\">https://doi.org/10.5220/0004366300770086</a>","bibtex":"@inproceedings{Böttcher_Feldotto_Hartel_2013, title={Schema-based Parallel Compression and Decompression of XML Data}, DOI={<a href=\"https://doi.org/10.5220/0004366300770086\">10.5220/0004366300770086</a>}, booktitle={WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013}, author={Böttcher, Stefan and Feldotto, Matthias and Hartel, Rita}, year={2013}, pages={77–86} }","ama":"Böttcher S, Feldotto M, Hartel R. Schema-based Parallel Compression and Decompression of XML Data. In: <i>WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013</i>. ; 2013:77-86. doi:<a href=\"https://doi.org/10.5220/0004366300770086\">10.5220/0004366300770086</a>","mla":"Böttcher, Stefan, et al. “Schema-Based Parallel Compression and Decompression of XML Data.” <i>WEBIST 2013 - Proceedings of the 9th International Conference on Web Information Systems and Technologies, Aachen, Germany, 8-10 May, 2013</i>, 2013, pp. 77–86, doi:<a href=\"https://doi.org/10.5220/0004366300770086\">10.5220/0004366300770086</a>."},"abstract":[{"lang":"eng","text":"Whenever huge amounts of XML data have to be transferred from a web server to multiple clients, the transferred data volumes can be reduced significantly by sending compressed XML instead of plain XML. Whenever applications require querying a compressed XML format and XML compression or decompression time is a bottleneck, parallel XML compression and parallel decompression may be of significant advantage. We choose the XML compressor XSDS as starting point for our new approach to parallel compression and parallel decompression of XML documents for the following reasons. First, XSDS generally reaches stronger compression ratios than other compressors like gzip, bzip2, and XMill. Second, in contrast to these compressors, XSDS not only supports XPath queries on compressed XML data, but also XPath queries can be evaluated on XSDS compressed data even faster than on uncompressed XML. We propose a String-search-based parsing approach to parallelize XML compression with XSDS, and we show that we can speed-up the compression of XML documents by a factor of 1.4 and that we can speed-up the decompression time even by a factor of up to 7 on a quad-core processor."}],"file":[{"date_created":"2018-10-31T17:00:33Z","creator":"feldi","file_id":"5229","content_type":"application/pdf","success":1,"relation":"main_file","date_updated":"2018-10-31T17:00:33Z","file_name":"WEBIST_2013_63.pdf","access_level":"closed","file_size":402400}],"date_created":"2018-01-05T08:35:39Z","type":"conference","department":[{"_id":"69"}]},{"abstract":[{"lang":"eng","text":"The accuracy of automatic speech recognition systems in noisy and reverberant environments can be improved notably by exploiting the uncertainty of the estimated speech features using so-called uncertainty-of-observation techniques. In this paper, we introduce a new Bayesian decision rule that can serve as a mathematical framework from which both known and new uncertainty-of-observation techniques can be either derived or approximated. The new decision rule in its direct form leads to the new significance decoding approach for Gaussian mixture models, which results in better performance compared to standard uncertainty-of-observation techniques in different additive and convolutive noise scenarios."}],"publication":"Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on","citation":{"apa":"Abdelaziz, A. H., Zeiler, S., Kolossa, D., Leutnant, V., &#38; Haeb-Umbach, R. (2013). GMM-based significance decoding. In <i>Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on</i> (pp. 6827–6831). <a href=\"https://doi.org/10.1109/ICASSP.2013.6638984\">https://doi.org/10.1109/ICASSP.2013.6638984</a>","ieee":"A. H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, and R. Haeb-Umbach, “GMM-based significance decoding,” in <i>Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on</i>, 2013, pp. 6827–6831.","chicago":"Abdelaziz, Ahmed H., Steffen Zeiler, Dorothea Kolossa, Volker Leutnant, and Reinhold Haeb-Umbach. “GMM-Based Significance Decoding.” In <i>Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On</i>, 6827–31, 2013. <a href=\"https://doi.org/10.1109/ICASSP.2013.6638984\">https://doi.org/10.1109/ICASSP.2013.6638984</a>.","short":"A.H. Abdelaziz, S. Zeiler, D. Kolossa, V. Leutnant, R. Haeb-Umbach, in: Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On, 2013, pp. 6827–6831.","mla":"Abdelaziz, Ahmed H., et al. “GMM-Based Significance Decoding.” <i>Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On</i>, 2013, pp. 6827–31, doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6638984\">10.1109/ICASSP.2013.6638984</a>.","ama":"Abdelaziz AH, Zeiler S, Kolossa D, Leutnant V, Haeb-Umbach R. GMM-based significance decoding. In: <i>Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference On</i>. ; 2013:6827-6831. doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6638984\">10.1109/ICASSP.2013.6638984</a>","bibtex":"@inproceedings{Abdelaziz_Zeiler_Kolossa_Leutnant_Haeb-Umbach_2013, title={GMM-based significance decoding}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2013.6638984\">10.1109/ICASSP.2013.6638984</a>}, booktitle={Acoustics, Speech and Signal Processing (ICASSP), 2013 IEEE International Conference on}, author={Abdelaziz, Ahmed H. and Zeiler, Steffen and Kolossa, Dorothea and Leutnant, Volker and Haeb-Umbach, Reinhold}, year={2013}, pages={6827–6831} }"},"type":"conference","keyword":["Bayes methods","Gaussian processes","convolution","decision theory","decoding","noise","reverberation","speech coding","speech recognition","Bayesian decision rule","GMM","Gaussian mixture models","additive noise scenarios","automatic speech recognition systems","convolutive noise scenarios","decoding approach","mathematical framework","reverberant environments","significance decoding","speech feature estimation","uncertainty-of-observation techniques","Hidden Markov models","Maximum likelihood decoding","Noise","Speech","Speech recognition","Uncertainty","Uncertainty-of-observation","modified imputation","noise robust speech recognition","significance decoding","uncertainty decoding"],"department":[{"_id":"54"}],"date_created":"2019-07-12T05:26:53Z","date_updated":"2022-01-06T06:51:07Z","title":"GMM-based significance decoding","year":"2013","status":"public","publication_identifier":{"issn":["1520-6149"]},"author":[{"last_name":"Abdelaziz","first_name":"Ahmed H.","full_name":"Abdelaziz, Ahmed H."},{"full_name":"Zeiler, Steffen","last_name":"Zeiler","first_name":"Steffen"},{"first_name":"Dorothea","last_name":"Kolossa","full_name":"Kolossa, Dorothea"},{"first_name":"Volker","last_name":"Leutnant","full_name":"Leutnant, Volker"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"user_id":"44006","doi":"10.1109/ICASSP.2013.6638984","page":"6827-6831","_id":"11716","language":[{"iso":"eng"}]},{"related_material":{"link":[{"relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13_Poster.pdf","description":"Poster"}]},"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."}],"publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)","type":"conference","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"],"department":[{"_id":"54"}],"date_created":"2019-07-12T05:27:20Z","date_updated":"2022-01-06T06:51:08Z","year":"2013","title":"MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations","publication_identifier":{"issn":["1520-6149"]},"author":[{"full_name":"Chinaev, Aleksej","last_name":"Chinaev","first_name":"Aleksej"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"doi":"10.1109/ICASSP.2013.6638279","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHa13.pdf"}],"language":[{"iso":"eng"}],"citation":{"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 <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013, pp. 3352–3356.","apa":"Chinaev, A., &#38; Haeb-Umbach, R. (2013). MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations. In <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i> (pp. 3352–3356). <a href=\"https://doi.org/10.1109/ICASSP.2013.6638279\">https://doi.org/10.1109/ICASSP.2013.6638279</a>","mla":"Chinaev, Aleksej, and Reinhold Haeb-Umbach. “MAP-Based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations.” <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013, pp. 3352–56, doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6638279\">10.1109/ICASSP.2013.6638279</a>.","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={<a href=\"https://doi.org/10.1109/ICASSP.2013.6638279\">10.1109/ICASSP.2013.6638279</a>}, booktitle={38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold}, year={2013}, pages={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 <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 3352–56, 2013. <a href=\"https://doi.org/10.1109/ICASSP.2013.6638279\">https://doi.org/10.1109/ICASSP.2013.6638279</a>.","short":"A. Chinaev, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 3352–3356.","ama":"Chinaev A, Haeb-Umbach R. MAP-based Estimation of the Parameters of a Gaussian Mixture Model in the Presence of Noisy Observations. In: <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>. ; 2013:3352-3356. doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6638279\">10.1109/ICASSP.2013.6638279</a>"},"oa":"1","status":"public","user_id":"44006","page":"3352-3356","_id":"11740"},{"doi":"10.1109/ICASSP.2013.6639116","user_id":"44006","language":[{"iso":"eng"}],"_id":"11742","page":"7477-7481","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHaTaRa13.pdf"}],"date_updated":"2022-01-06T06:51:08Z","publication_identifier":{"issn":["1520-6149"]},"author":[{"full_name":"Chinaev, Aleksej","last_name":"Chinaev","first_name":"Aleksej"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"},{"first_name":"Jalal","last_name":"Taghia","full_name":"Taghia, Jalal"},{"full_name":"Martin, Rainer","first_name":"Rainer","last_name":"Martin"}],"year":"2013","title":"Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor","status":"public","oa":"1","department":[{"_id":"54"}],"type":"conference","date_created":"2019-07-12T05:27:23Z","related_material":{"link":[{"description":"Poster","url":"https://groups.uni-paderborn.de/nt/pubs/2013/ChHaTaRa13_Poster.pdf","relation":"supplementary_material"}]},"abstract":[{"text":"In this paper we present an improved version of the recently proposed Maximum A-Posteriori (MAP) based noise power spectral density estimator. An empirical bias compensation and bandwidth adjustment reduce bias and variance of the noise variance estimates. The main advantage of the MAP-based postprocessor is its low estimation variance. The estimator is employed in the second stage of a two-stage single-channel speech enhancement system, where eight different state-of-the-art noise tracking algorithms were tested in the first stage. While the postprocessor hardly affects the results in stationary noise scenarios, it becomes the more effective the more nonstationary the noise is. The proposed postprocessor was able to improve all systems in babble noise w.r.t. the perceptual evaluation of speech quality performance.","lang":"eng"}],"citation":{"chicago":"Chinaev, Aleksej, Reinhold Haeb-Umbach, Jalal Taghia, and Rainer Martin. “Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-Based Postprocessor.” In <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 7477–81, 2013. <a href=\"https://doi.org/10.1109/ICASSP.2013.6639116\">https://doi.org/10.1109/ICASSP.2013.6639116</a>.","short":"A. Chinaev, R. Haeb-Umbach, J. Taghia, R. Martin, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 7477–7481.","apa":"Chinaev, A., Haeb-Umbach, R., Taghia, J., &#38; Martin, R. (2013). Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor. In <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i> (pp. 7477–7481). <a href=\"https://doi.org/10.1109/ICASSP.2013.6639116\">https://doi.org/10.1109/ICASSP.2013.6639116</a>","ieee":"A. Chinaev, R. Haeb-Umbach, J. Taghia, and R. Martin, “Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor,” in <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013, pp. 7477–7481.","ama":"Chinaev A, Haeb-Umbach R, Taghia J, Martin R. Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor. In: <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>. ; 2013:7477-7481. doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6639116\">10.1109/ICASSP.2013.6639116</a>","bibtex":"@inproceedings{Chinaev_Haeb-Umbach_Taghia_Martin_2013, title={Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-based Postprocessor}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2013.6639116\">10.1109/ICASSP.2013.6639116</a>}, booktitle={38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)}, author={Chinaev, Aleksej and Haeb-Umbach, Reinhold and Taghia, Jalal and Martin, Rainer}, year={2013}, pages={7477–7481} }","mla":"Chinaev, Aleksej, et al. “Improved Single-Channel Nonstationary Noise Tracking by an Optimized MAP-Based Postprocessor.” <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013, pp. 7477–81, doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6639116\">10.1109/ICASSP.2013.6639116</a>."},"publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)"},{"type":"conference","oa":"1","department":[{"_id":"54"}],"date_created":"2019-07-12T05:27:46Z","abstract":[{"lang":"eng","text":"Among the different configurations of multi-microphone systems, e.g., in applications of speech dereverberation or denoising, we consider the case without a priori information of the microphone-array geometry. This naturally invokes explicit or implicit identification of source-receiver transfer functions as an indirect description of the microphone-array configuration. However, this blind channel identification (BCI) has been difficult due to the lack of unique identifiability in the presence of observation noise or near-common channel zeros. In this paper, we study the implicit BCI performance of blind signal enhancement techniques such as the adaptive principal component analysis (PCA) or the iterative blind equalization and channel identification (BENCH). To this end, we make use of a recently proposed metric, the normalized filter-projection misalignment (NFPM), which is tailored for BCI evaluation in ill-conditioned (e.g., noisy) scenarios. The resulting understanding of implicit BCI performance can help to judge the behavior of multi-microphone speech enhancement systems and the suitability of implicit BCI to serve channel-based (i.e., channel-informed) enhancement."}],"publication":"21th European Signal Processing Conference (EUSIPCO 2013)","citation":{"chicago":"Enzner, Gerald, Dominic Schmid, and Reinhold Haeb-Umbach. “On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques.” In <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.","ama":"Enzner G, Schmid D, Haeb-Umbach R. On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques. In: <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>. ; 2013.","short":"G. Enzner, D. Schmid, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013.","bibtex":"@inproceedings{Enzner_Schmid_Haeb-Umbach_2013, title={On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques}, booktitle={21th European Signal Processing Conference (EUSIPCO 2013)}, author={Enzner, Gerald and Schmid, Dominic and Haeb-Umbach, Reinhold}, year={2013} }","apa":"Enzner, G., Schmid, D., &#38; Haeb-Umbach, R. (2013). On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques. In <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>.","mla":"Enzner, Gerald, et al. “On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques.” <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.","ieee":"G. Enzner, D. Schmid, and R. Haeb-Umbach, “On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques,” in <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>, 2013."},"user_id":"44006","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/EnScHa2013.pdf"}],"_id":"11762","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:08Z","title":"On the Acoustic Channel Identification in Multi-Microphone Systems via Adaptive Blind Signal Enhancement Techniques","status":"public","year":"2013","author":[{"full_name":"Enzner, Gerald","first_name":"Gerald","last_name":"Enzner"},{"full_name":"Schmid, Dominic","first_name":"Dominic","last_name":"Schmid"},{"last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold","id":"242"}]},{"publication":"Automatic Speech Recognition and Understanding Workshop (ASRU 2013)","citation":{"bibtex":"@inproceedings{Heymann_Walter_Haeb-Umbach_Raj_2013, title={Unsupervised Word Segmentation from Noisy Input}, booktitle={Automatic Speech Recognition and Understanding Workshop (ASRU 2013)}, author={Heymann, Jahn and Walter, Oliver and Haeb-Umbach, Reinhold and Raj, Bhiksha}, year={2013} }","ama":"Heymann J, Walter O, Haeb-Umbach R, Raj B. Unsupervised Word Segmentation from Noisy Input. In: <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>. ; 2013.","mla":"Heymann, Jahn, et al. “Unsupervised Word Segmentation from Noisy Input.” <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>, 2013.","short":"J. Heymann, O. Walter, R. Haeb-Umbach, B. Raj, in: Automatic Speech Recognition and Understanding Workshop (ASRU 2013), 2013.","chicago":"Heymann, Jahn, Oliver Walter, Reinhold Haeb-Umbach, and Bhiksha Raj. “Unsupervised Word Segmentation from Noisy Input.” In <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>, 2013.","ieee":"J. Heymann, O. Walter, R. Haeb-Umbach, and B. Raj, “Unsupervised Word Segmentation from Noisy Input,” in <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>, 2013.","apa":"Heymann, J., Walter, O., Haeb-Umbach, R., &#38; Raj, B. (2013). Unsupervised Word Segmentation from Noisy Input. In <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>."},"related_material":{"link":[{"relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HeWaHaRa_Poster.pdf","description":"Poster"}]},"date_created":"2019-07-12T05:28:47Z","type":"conference","department":[{"_id":"54"}],"oa":"1","year":"2013","status":"public","title":"Unsupervised Word Segmentation from Noisy Input","author":[{"id":"9168","full_name":"Heymann, Jahn","first_name":"Jahn","last_name":"Heymann"},{"first_name":"Oliver","last_name":"Walter","full_name":"Walter, Oliver"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"},{"full_name":"Raj, Bhiksha","first_name":"Bhiksha","last_name":"Raj"}],"date_updated":"2022-01-06T06:51:09Z","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HeWaHaRa13.pdf"}],"_id":"11815","language":[{"iso":"eng"}],"user_id":"44006"},{"citation":{"bibtex":"@inproceedings{Hoang_Haeb-Umbach_2013, title={Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2013.6638353\">10.1109/ICASSP.2013.6638353</a>}, booktitle={38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)}, author={Hoang, Manh Kha and Haeb-Umbach, Reinhold}, year={2013}, pages={3721–3725} }","ama":"Hoang MK, Haeb-Umbach R. Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning. In: <i>38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>. ; 2013:3721-3725. doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6638353\">10.1109/ICASSP.2013.6638353</a>","short":"M.K. Hoang, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013), 2013, pp. 3721–3725.","chicago":"Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification of Censored Gaussian Data with Application to WiFi Indoor Positioning.” In <i>38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>, 3721–25, 2013. <a href=\"https://doi.org/10.1109/ICASSP.2013.6638353\">https://doi.org/10.1109/ICASSP.2013.6638353</a>.","ieee":"M. K. Hoang and R. Haeb-Umbach, “Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning,” in <i>38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>, 2013, pp. 3721–3725.","mla":"Hoang, Manh Kha, and Reinhold Haeb-Umbach. “Parameter Estimation and Classification of Censored Gaussian Data with Application to WiFi Indoor Positioning.” <i>38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i>, 2013, pp. 3721–25, doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6638353\">10.1109/ICASSP.2013.6638353</a>.","apa":"Hoang, M. K., &#38; Haeb-Umbach, R. (2013). Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning. In <i>38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)</i> (pp. 3721–3725). <a href=\"https://doi.org/10.1109/ICASSP.2013.6638353\">https://doi.org/10.1109/ICASSP.2013.6638353</a>"},"oa":"1","status":"public","user_id":"44006","page":"3721-3725","_id":"11816","abstract":[{"text":"In this paper, we consider the Maximum Likelihood (ML) estimation of the parameters of a GAUSSIAN in the presence of censored, i.e., clipped data. We show that the resulting Expectation Maximization (EM) algorithm delivers virtually biasfree and efficient estimates, and we discuss its convergence properties. We also discuss optimal classification in the presence of censored data. Censored data are frequently encountered in wireless LAN positioning systems based on the fingerprinting method employing signal strength measurements, due to the limited sensitivity of the portable devices. Experiments both on simulated and real-world data demonstrate the effectiveness of the proposed algorithms.","lang":"eng"}],"related_material":{"link":[{"description":"Poster","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013_Poster.pdf","relation":"supplementary_material"}]},"publication":"38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)","keyword":["Gaussian processes","Global Positioning System","convergence","expectation-maximisation algorithm","fingerprint identification","indoor radio","signal classification","wireless LAN","EM algorithm","ML estimation","WiFi indoor positioning","censored Gaussian data classification","clipped data","convergence properties","expectation maximization algorithm","fingerprinting method","maximum likelihood estimation","optimal classification","parameters estimation","portable devices sensitivity","signal strength measurements","wireless LAN positioning systems","Convergence","IEEE 802.11 Standards","Maximum likelihood estimation","Parameter estimation","Position measurement","Training","Indoor positioning","censored data","expectation maximization","signal strength","wireless LAN"],"type":"conference","department":[{"_id":"54"}],"date_created":"2019-07-12T05:28:48Z","date_updated":"2022-01-06T06:51:09Z","year":"2013","title":"Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning","author":[{"last_name":"Hoang","first_name":"Manh Kha","full_name":"Hoang, Manh Kha"},{"id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold"}],"publication_identifier":{"issn":["1520-6149"]},"doi":"10.1109/ICASSP.2013.6638353","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/HoHa2013.pdf"}],"language":[{"iso":"eng"}]},{"abstract":[{"lang":"eng","text":"Recently, substantial progress has been made in the field of reverberant speech signal processing, including both single- and multichannel de-reverberation techniques, and automatic speech recognition (ASR) techniques robust to reverberation. To evaluate state-of-the-art algorithms and obtain new insights regarding potential future research directions, we propose a common evaluation framework including datasets, tasks, and evaluation metrics for both speech enhancement and ASR techniques. The proposed framework will be used as a common basis for the REVERB (REverberant Voice Enhancement and Recognition Benchmark) challenge. This paper describes the rationale behind the challenge, and provides a detailed description of the evaluation framework and benchmark results."}],"citation":{"ieee":"K. Kinoshita <i>et al.</i>, “The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech,” in <i> IEEE Workshop on Applications of Signal Processing to Audio and Acoustics </i>, 2013, pp. 22–23.","apa":"Kinoshita, K., Delcroix, M., Yoshioka, T., Nakatani, T., Habets, E., Haeb-Umbach, R., … Raj, B. (2013). The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech. In <i> IEEE Workshop on Applications of Signal Processing to Audio and Acoustics </i> (pp. 22–23).","chicago":"Kinoshita, Keisuke, Marc Delcroix, Takuya Yoshioka, Tomohiro Nakatani, Emanuel Habets, Reinhold Haeb-Umbach, Volker Leutnant, et al. “The Reverb Challenge: A Common Evaluation Framework for Dereverberation and Recognition of Reverberant Speech.” In <i> IEEE Workshop on Applications of Signal Processing to Audio and Acoustics </i>, 22–23, 2013.","short":"K. Kinoshita, M. Delcroix, T. Yoshioka, T. Nakatani, E. Habets, R. Haeb-Umbach, V. Leutnant, A. Sehr, W. Kellermann, R. Maas, S. Gannot, B. Raj, in:  IEEE Workshop on Applications of Signal Processing to Audio and Acoustics , 2013, pp. 22–23.","mla":"Kinoshita, Keisuke, et al. “The Reverb Challenge: A Common Evaluation Framework for Dereverberation and Recognition of Reverberant Speech.” <i> IEEE Workshop on Applications of Signal Processing to Audio and Acoustics </i>, 2013, pp. 22–23.","bibtex":"@inproceedings{Kinoshita_Delcroix_Yoshioka_Nakatani_Habets_Haeb-Umbach_Leutnant_Sehr_Kellermann_Maas_et al._2013, title={The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech}, booktitle={ IEEE Workshop on Applications of Signal Processing to Audio and Acoustics }, author={Kinoshita, Keisuke and Delcroix, Marc and Yoshioka, Takuya and Nakatani, Tomohiro and Habets, Emanuel and Haeb-Umbach, Reinhold and Leutnant, Volker and Sehr, Armin and Kellermann, Walter and Maas, Roland and et al.}, year={2013}, pages={22–23} }","ama":"Kinoshita K, Delcroix M, Yoshioka T, et al. The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech. In: <i> IEEE Workshop on Applications of Signal Processing to Audio and Acoustics </i>. ; 2013:22-23."},"publication":" IEEE Workshop on Applications of Signal Processing to Audio and Acoustics ","oa":"1","department":[{"_id":"54"}],"type":"conference","keyword":["Reverberant speech","dereverberation","ASR","evaluation","challenge"],"date_created":"2019-07-12T05:29:17Z","date_updated":"2022-01-06T06:51:11Z","author":[{"first_name":"Keisuke","last_name":"Kinoshita","full_name":"Kinoshita, Keisuke"},{"full_name":"Delcroix, Marc","first_name":"Marc","last_name":"Delcroix"},{"full_name":"Yoshioka, Takuya","last_name":"Yoshioka","first_name":"Takuya"},{"first_name":"Tomohiro","last_name":"Nakatani","full_name":"Nakatani, Tomohiro"},{"full_name":"Habets, Emanuel","first_name":"Emanuel","last_name":"Habets"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach"},{"last_name":"Leutnant","first_name":"Volker","full_name":"Leutnant, Volker"},{"full_name":"Sehr, Armin","last_name":"Sehr","first_name":"Armin"},{"first_name":"Walter","last_name":"Kellermann","full_name":"Kellermann, Walter"},{"full_name":"Maas, Roland","last_name":"Maas","first_name":"Roland"},{"full_name":"Gannot, Sharon","last_name":"Gannot","first_name":"Sharon"},{"full_name":"Raj, Bhiksha","last_name":"Raj","first_name":"Bhiksha"}],"title":"The reverb challenge: a common evaluation framework for dereverberation and recognition of reverberant speech","status":"public","year":"2013","user_id":"44006","language":[{"iso":"eng"}],"_id":"11841","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2013/Reverb2013.pdf"}],"page":" 22-23 "},{"type":"journal_article","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"],"department":[{"_id":"54"}],"date_created":"2019-07-12T05:29:42Z","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."}],"publication":"IEEE Transactions on Audio, Speech, and Language Processing","issue":"8","citation":{"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.","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.","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>.","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>"},"user_id":"44006","doi":"10.1109/TASL.2013.2258013","volume":21,"page":"1640-1652","_id":"11862","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:11Z","intvolume":"        21","title":"Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition","year":"2013","status":"public","author":[{"last_name":"Leutnant","first_name":"Volker","full_name":"Leutnant, Volker"},{"full_name":"Krueger, Alexander","last_name":"Krueger","first_name":"Alexander"},{"full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold","id":"242"}]},{"citation":{"mla":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs.” <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.","bibtex":"@inproceedings{Tran Vu_Haeb-Umbach_2013, title={Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs}, booktitle={21th European Signal Processing Conference (EUSIPCO 2013)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2013} }","ama":"Tran Vu DH, Haeb-Umbach R. Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs. In: <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>. ; 2013.","ieee":"D. H. Tran Vu and R. Haeb-Umbach, “Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs,” in <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.","apa":"Tran Vu, D. H., &#38; Haeb-Umbach, R. (2013). Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs. In <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>.","chicago":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs.” In <i>21th European Signal Processing Conference (EUSIPCO 2013)</i>, 2013.","short":"D.H. Tran Vu, R. Haeb-Umbach, in: 21th European Signal Processing Conference (EUSIPCO 2013), 2013."},"publication":"21th European Signal Processing Conference (EUSIPCO 2013)","related_material":{"link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/TrHa2013_01_Presentation.pdf","relation":"supplementary_material","description":"Presentation"}]},"abstract":[{"text":"We present a novel method to exploit correlations of adjacent time-frequency (TF)-slots for a sparseness-based blind speech separation (BSS) system. Usually, these correlations are exploited by some heuristic smoothing techniques in the post-processing of the estimated soft TF masks. We propose a different approach: Based on our previous work with one-dimensional (1D)-hidden Markov models (HMMs) along the time axis we extend the modeling to two-dimensional (2D)-HMMs to exploit both temporal and spectral correlations in the speech signal. Based on the principles of turbo decoding we solved the complex inference of 2D-HMMs by a modified forward-backward algorithm which operates alternatingly along the time and the frequency axis. Extrinsic information is exchanged between these steps such that increasingly better soft time-frequency masks are obtained, leading to improved speech separation performance in highly reverberant recording conditions.","lang":"eng"}],"date_created":"2019-07-12T05:30:36Z","department":[{"_id":"54"}],"oa":"1","type":"conference","author":[{"full_name":"Tran Vu, Dang Hai","last_name":"Tran Vu","first_name":"Dang Hai"},{"id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold"}],"status":"public","year":"2013","title":"Blind Speech Separation Exploiting Temporal and Spectral Correlations Using Turbo Decoding of 2D-HMMs","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"_id":"11909","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/TrHa2013_01.pdf","open_access":"1"}],"user_id":"44006"},{"abstract":[{"lang":"eng","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."}],"citation":{"bibtex":"@inproceedings{Vu_Haeb-Umbach_2013, title={Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation}, DOI={<a href=\"https://doi.org/10.1109/ICASSP.2013.6637771\">10.1109/ICASSP.2013.6637771</a>}, 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} }","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 <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 863–67, 2013. <a href=\"https://doi.org/10.1109/ICASSP.2013.6637771\">https://doi.org/10.1109/ICASSP.2013.6637771</a>.","short":"D.H.T. Vu, R. Haeb-Umbach, in: 38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013), 2013, pp. 863–867.","ama":"Vu DHT, Haeb-Umbach R. Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation. In: <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>. ; 2013:863-867. doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6637771\">10.1109/ICASSP.2013.6637771</a>","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 <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013, pp. 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.” <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i>, 2013, pp. 863–67, doi:<a href=\"https://doi.org/10.1109/ICASSP.2013.6637771\">10.1109/ICASSP.2013.6637771</a>.","apa":"Vu, D. H. T., &#38; Haeb-Umbach, R. (2013). Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation. In <i>38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)</i> (pp. 863–867). <a href=\"https://doi.org/10.1109/ICASSP.2013.6637771\">https://doi.org/10.1109/ICASSP.2013.6637771</a>"},"publication":"38th International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013)","department":[{"_id":"54"}],"type":"conference","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"],"date_created":"2019-07-12T05:30:45Z","date_updated":"2022-01-06T06:51:12Z","author":[{"full_name":"Vu, Dang Hai Tran","first_name":"Dang Hai Tran","last_name":"Vu"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"publication_identifier":{"issn":["1520-6149"]},"year":"2013","status":"public","title":"Using the turbo principle for exploiting temporal and spectral correlations in speech presence probability estimation","user_id":"44006","doi":"10.1109/ICASSP.2013.6637771","_id":"11917","language":[{"iso":"eng"}],"page":"863-867"},{"citation":{"mla":"Walter, Oliver, et al. “Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling.” <i>IEEE International Conference on Robotics and Automation (ICRA 2013)</i>, 2013.","ama":"Walter O, Haeb-Umbach R, Chaudhuri S, Raj B. Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling. In: <i>IEEE International Conference on Robotics and Automation (ICRA 2013)</i>. ; 2013.","bibtex":"@inproceedings{Walter_Haeb-Umbach_Chaudhuri_Raj_2013, title={Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling}, booktitle={IEEE International Conference on Robotics and Automation (ICRA 2013)}, author={Walter, Oliver and Haeb-Umbach, Reinhold and Chaudhuri, Sourish and Raj, Bhiksha}, year={2013} }","apa":"Walter, O., Haeb-Umbach, R., Chaudhuri, S., &#38; Raj, B. (2013). Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling. In <i>IEEE International Conference on Robotics and Automation (ICRA 2013)</i>.","ieee":"O. Walter, R. Haeb-Umbach, S. Chaudhuri, and B. Raj, “Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling,” in <i>IEEE International Conference on Robotics and Automation (ICRA 2013)</i>, 2013.","short":"O. Walter, R. Haeb-Umbach, S. Chaudhuri, B. Raj, in: IEEE International Conference on Robotics and Automation (ICRA 2013), 2013.","chicago":"Walter, Oliver, Reinhold Haeb-Umbach, Sourish Chaudhuri, and Bhiksha Raj. “Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling.” In <i>IEEE International Conference on Robotics and Automation (ICRA 2013)</i>, 2013."},"publication":"IEEE International Conference on Robotics and Automation (ICRA 2013)","abstract":[{"lang":"eng","text":"In this paper we consider the unsupervised word discovery from phonetic input. We employ a word segmentation algorithm which simultaneously develops a lexicon, i.e., the transcription of a word in terms of a phone sequence, learns a n-gram language model describing word and word sequence probabilities, and carries out the segmentation itself. The underlying statistical model is that of a Pitman-Yor process, a concept known from Bayesian non-parametrics, which allows for an a priori unknown and unlimited number of different words. Using a hierarchy of Pitman-Yor processes, language models of different order can be employed and nesting it with another hierarchy of Pitman-Yor processes on the phone level allows for backing off unknown word unigrams by phone m-grams. We present results on a large-vocabulary task, assuming an error-free phone sequence is given. We finish by discussing options how to cope with noisy phone sequences."}],"related_material":{"link":[{"relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaHaChRa2013_Poster.pdf","description":"Poster"},{"relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaHaChRa2013_Spotlight.pdf","description":"Spotlight"}]},"date_created":"2019-07-12T05:30:50Z","department":[{"_id":"54"}],"oa":"1","type":"conference","author":[{"full_name":"Walter, Oliver","last_name":"Walter","first_name":"Oliver"},{"id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold"},{"last_name":"Chaudhuri","first_name":"Sourish","full_name":"Chaudhuri, Sourish"},{"full_name":"Raj, Bhiksha","last_name":"Raj","first_name":"Bhiksha"}],"year":"2013","title":"Unsupervised Word Discovery from Phonetic Input Using Nested Pitman-Yor Language Modeling","status":"public","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"_id":"11921","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaHaChRa2013.pdf","open_access":"1"}],"user_id":"44006"},{"date_created":"2019-07-12T05:30:53Z","oa":"1","department":[{"_id":"54"}],"type":"conference","citation":{"short":"O. Walter, T. Korthals, R. Haeb-Umbach, B. Raj, in: Automatic Speech Recognition and Understanding Workshop (ASRU 2013), 2013.","chicago":"Walter, Oliver, Timo Korthals, Reinhold Haeb-Umbach, and Bhiksha Raj. “Hierarchical System for Word Discovery Exploiting DTW-Based Initialization.” In <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>, 2013.","apa":"Walter, O., Korthals, T., Haeb-Umbach, R., &#38; Raj, B. (2013). Hierarchical System for Word Discovery Exploiting DTW-Based Initialization. In <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>.","ieee":"O. Walter, T. Korthals, R. Haeb-Umbach, and B. Raj, “Hierarchical System for Word Discovery Exploiting DTW-Based Initialization,” in <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>, 2013.","ama":"Walter O, Korthals T, Haeb-Umbach R, Raj B. Hierarchical System for Word Discovery Exploiting DTW-Based Initialization. In: <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>. ; 2013.","bibtex":"@inproceedings{Walter_Korthals_Haeb-Umbach_Raj_2013, title={Hierarchical System for Word Discovery Exploiting DTW-Based Initialization}, booktitle={Automatic Speech Recognition and Understanding Workshop (ASRU 2013)}, author={Walter, Oliver and Korthals, Timo and Haeb-Umbach, Reinhold and Raj, Bhiksha}, year={2013} }","mla":"Walter, Oliver, et al. “Hierarchical System for Word Discovery Exploiting DTW-Based Initialization.” <i>Automatic Speech Recognition and Understanding Workshop (ASRU 2013)</i>, 2013."},"publication":"Automatic Speech Recognition and Understanding Workshop (ASRU 2013)","related_material":{"link":[{"relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaKoHaRa13_Award.pdf","description":"Award"},{"description":"Poster","relation":"supplementary_material","url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaKoHaRa13_Poster.pdf"}]},"_id":"11924","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaKoHaRa13.pdf","open_access":"1"}],"user_id":"44006","author":[{"first_name":"Oliver","last_name":"Walter","full_name":"Walter, Oliver"},{"full_name":"Korthals, Timo","first_name":"Timo","last_name":"Korthals"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"},{"last_name":"Raj","first_name":"Bhiksha","full_name":"Raj, Bhiksha"}],"title":"Hierarchical System for Word Discovery Exploiting DTW-Based Initialization","year":"2013","status":"public","date_updated":"2022-01-06T06:51:12Z"},{"abstract":[{"text":"In this paper we present a novel initialization method for unsupervised learning of acoustic patterns in recordings of continuous speech. The pattern discovery task is solved by dynamic time warping whose performance we improve by a smart starting point selection. This enables a more accurate discovery of patterns compared to conventional approaches. After graph-based clustering the patterns are employed for training hidden Markov models for an unsupervised speech acquisition. By iterating between model training and decoding in an EM-like framework the word accuracy is continuously improved. On the TIDIGITS corpus we achieve a word error rate of about 13 percent by the proposed unsupervised pattern discovery approach, which neither assumes knowledge of the acoustic units nor of the labels of the training data.","lang":"eng"}],"citation":{"short":"O. Walter, J. Schmalenstroeer, R. Haeb-Umbach, A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01), 2013.","chicago":"Walter, Oliver, Joerg Schmalenstroeer, and Reinhold Haeb-Umbach. <i>A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>, 2013.","ieee":"O. Walter, J. Schmalenstroeer, and R. Haeb-Umbach, <i>A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>. 2013.","apa":"Walter, O., Schmalenstroeer, J., &#38; Haeb-Umbach, R. (2013). <i>A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>.","bibtex":"@book{Walter_Schmalenstroeer_Haeb-Umbach_2013, title={A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)}, author={Walter, Oliver and Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}, year={2013} }","ama":"Walter O, Schmalenstroeer J, Haeb-Umbach R. <i>A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>.; 2013.","mla":"Walter, Oliver, et al. <i>A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)</i>. 2013."},"type":"report","department":[{"_id":"54"}],"oa":"1","date_created":"2019-07-12T05:30:55Z","date_updated":"2022-01-06T06:51:12Z","status":"public","title":"A Novel Initialization Method for Unsupervised Learning of Acoustic Patterns in Speech (FGNT-2013-01)","year":"2013","author":[{"last_name":"Walter","first_name":"Oliver","full_name":"Walter, Oliver"},{"full_name":"Schmalenstroeer, Joerg","first_name":"Joerg","last_name":"Schmalenstroeer","id":"460"},{"full_name":"Haeb-Umbach, Reinhold","first_name":"Reinhold","last_name":"Haeb-Umbach","id":"242"}],"user_id":"44006","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2013/WaScHa2013.pdf","open_access":"1"}],"_id":"11926","language":[{"iso":"eng"}]},{"department":[{"_id":"589"}],"type":"conference","date_created":"2019-07-18T09:51:24Z","citation":{"apa":"Bloessl, B., Segata, M., Sommer, C., &#38; Dressler, F. (2013). Decoding IEEE 802.11a/g/p OFDM in software using GNU radio. In <i>Proceedings of the 19th annual international conference on Mobile computing &#38; networking - MobiCom ’13</i>. <a href=\"https://doi.org/10.1145/2500423.2505300\">https://doi.org/10.1145/2500423.2505300</a>","mla":"Bloessl, Bastian, et al. “Decoding IEEE 802.11a/g/p OFDM in Software Using GNU Radio.” <i>Proceedings of the 19th Annual International Conference on Mobile Computing &#38; Networking - MobiCom ’13</i>, 2013, doi:<a href=\"https://doi.org/10.1145/2500423.2505300\">10.1145/2500423.2505300</a>.","ieee":"B. Bloessl, M. Segata, C. Sommer, and F. Dressler, “Decoding IEEE 802.11a/g/p OFDM in software using GNU radio,” in <i>Proceedings of the 19th annual international conference on Mobile computing &#38; networking - MobiCom ’13</i>, 2013.","chicago":"Bloessl, Bastian, Michele Segata, Christoph Sommer, and Falko Dressler. “Decoding IEEE 802.11a/g/p OFDM in Software Using GNU Radio.” In <i>Proceedings of the 19th Annual International Conference on Mobile Computing &#38; Networking - MobiCom ’13</i>, 2013. <a href=\"https://doi.org/10.1145/2500423.2505300\">https://doi.org/10.1145/2500423.2505300</a>.","ama":"Bloessl B, Segata M, Sommer C, Dressler F. Decoding IEEE 802.11a/g/p OFDM in software using GNU radio. In: <i>Proceedings of the 19th Annual International Conference on Mobile Computing &#38; Networking - MobiCom ’13</i>. ; 2013. doi:<a href=\"https://doi.org/10.1145/2500423.2505300\">10.1145/2500423.2505300</a>","short":"B. Bloessl, M. Segata, C. Sommer, F. Dressler, in: Proceedings of the 19th Annual International Conference on Mobile Computing &#38; Networking - MobiCom ’13, 2013.","bibtex":"@inproceedings{Bloessl_Segata_Sommer_Dressler_2013, title={Decoding IEEE 802.11a/g/p OFDM in software using GNU radio}, DOI={<a href=\"https://doi.org/10.1145/2500423.2505300\">10.1145/2500423.2505300</a>}, booktitle={Proceedings of the 19th annual international conference on Mobile computing &#38; networking - MobiCom ’13}, author={Bloessl, Bastian and Segata, Michele and Sommer, Christoph and Dressler, Falko}, year={2013} }"},"publication":"Proceedings of the 19th annual international conference on Mobile computing & networking - MobiCom '13","user_id":"49154","doi":"10.1145/2500423.2505300","_id":"11976","language":[{"iso":"eng"}],"publication_status":"published","date_updated":"2022-01-06T06:51:14Z","publication_identifier":{"isbn":["9781450319997"]},"author":[{"full_name":"Bloessl, Bastian","last_name":"Bloessl","first_name":"Bastian"},{"first_name":"Michele","last_name":"Segata","full_name":"Segata, Michele"},{"full_name":"Sommer, Christoph","orcid":"0000-0002-4336-7350","last_name":"Sommer","first_name":"Christoph","id":"49154"},{"full_name":"Dressler, Falko","last_name":"Dressler","first_name":"Falko"}],"status":"public","year":"2013","title":"Decoding IEEE 802.11a/g/p OFDM in software using GNU radio"}]