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Evaluation experiments show high efficiency of information access to the generated documents.","lang":"eng"}],"publication":"Research in Computing Science","department":[{"_id":"36"},{"_id":"1"},{"_id":"579"}],"type":"journal_article","date_created":"2018-02-12T11:24:37Z","article_type":"original","intvolume":"        33","publication_status":"published","date_updated":"2022-01-06T06:51:06Z","publication_identifier":{"issn":["1870-4069"]},"author":[{"full_name":"Bsiri, Sandra","first_name":"Sandra","last_name":"Bsiri"},{"orcid":"0000-0002-8180-5606","first_name":"Michaela","last_name":"Geierhos","full_name":"Geierhos, Michaela","id":"42496"},{"first_name":"Christoph","last_name":"Ringlstetter","full_name":"Ringlstetter, Christoph"}],"year":"2008","title":"Structuring Job Search via Local Grammars","language":[{"iso":"eng"}],"main_file_link":[{"url":"https://www.cicling.org/2008/RCS-vol-33/16-Bsiri.pdf","open_access":"1"}]},{"date_created":"2019-07-12T05:28:02Z","oa":"1","department":[{"_id":"54"}],"type":"journal_article","citation":{"bibtex":"@article{Haeb-Umbach_2008, title={Uncertainty Decoding in Automatic Speech Recognition}, journal={2008 ITG Conference on Voice Communication (SprachKommunikation)}, author={Haeb-Umbach, Reinhold}, year={2008}, pages={1–7} }","ama":"Haeb-Umbach R. 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The usefulness of the presented statistical framework is then exemplified for two types of realworld problems: The first is improving the robustness of speech recognition towards incomplete or corrupted feature vectors due to a lossy communication link between the speech capturing front end and the backend recognition engine. And the second is the well-known and extensively studied issue of improving the robustness of the recognizer towards environmental noise.","lang":"eng"}],"_id":"11776","language":[{"iso":"eng"}],"page":"1-7","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2008/Ha08.pdf","open_access":"1"}],"user_id":"44006","author":[{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"title":"Uncertainty Decoding in Automatic Speech Recognition","year":"2008","status":"public","date_updated":"2022-01-06T06:51:08Z"},{"oa":"1","citation":{"short":"R. Haeb-Umbach, V. Ion, in: B. Lindenberg, Z.-H. Tan (Eds.), Automatic Speech Recognition on Mobile Devices and over Communication Networks, Springer, 2008, pp. 187–210.","chicago":"Haeb-Umbach, Reinhold, and Valentin Ion. “Error Concealement.” In <i>Automatic Speech Recognition on Mobile Devices and over Communication Networks</i>, edited by Borge Lindenberg and Zheng-Hua Tan, Advances in Computer Vision and Pattern Recognition:187–210. Advances in Pattern Recognition. Springer, 2008.","apa":"Haeb-Umbach, R., &#38; Ion, V. (2008). Error Concealement. In B. Lindenberg &#38; Z.-H. Tan (Eds.), <i>Automatic Speech Recognition on Mobile Devices and over Communication Networks</i> (Vol. Advances in Computer Vision and Pattern Recognition, pp. 187–210). Springer.","ieee":"R. Haeb-Umbach and V. Ion, “Error Concealement,” in <i>Automatic Speech Recognition on Mobile Devices and over Communication Networks</i>, vol. Advances in Computer Vision and Pattern Recognition, B. Lindenberg and Z.-H. Tan, Eds. Springer, 2008, pp. 187–210.","ama":"Haeb-Umbach R, Ion V. Error Concealement. In: Lindenberg B, Tan Z-H, eds. <i>Automatic Speech Recognition on Mobile Devices and over Communication Networks</i>. Vol Advances in Computer Vision and Pattern Recognition. Advances in Pattern Recognition. Springer; 2008:187-210.","bibtex":"@inbook{Haeb-Umbach_Ion_2008, series={Advances in Pattern Recognition}, title={Error Concealement}, volume={Advances in Computer Vision and Pattern Recognition}, booktitle={Automatic Speech Recognition on Mobile Devices and over Communication Networks}, publisher={Springer}, author={Haeb-Umbach, Reinhold and Ion, Valentin}, editor={Lindenberg, Borge and Tan, Zheng-HuaEditors}, year={2008}, pages={187–210}, collection={Advances in Pattern Recognition} }","mla":"Haeb-Umbach, Reinhold, and Valentin Ion. “Error Concealement.” <i>Automatic Speech Recognition on Mobile Devices and over Communication Networks</i>, edited by Borge Lindenberg and Zheng-Hua Tan, vol. Advances in Computer Vision and Pattern Recognition, Springer, 2008, pp. 187–210."},"user_id":"44006","editor":[{"first_name":"Borge","last_name":"Lindenberg","full_name":"Lindenberg, Borge"},{"full_name":"Tan, Zheng-Hua","first_name":"Zheng-Hua","last_name":"Tan"}],"volume":"Advances in Computer Vision and Pattern Recognition","page":"187-210","_id":"11789","publisher":"Springer","status":"public","type":"book_chapter","department":[{"_id":"54"}],"date_created":"2019-07-12T05:28:17Z","abstract":[{"text":"In distributed and network speech recognition the actual recognition task is not carried out on the user{\\rq}s terminal but rather on a remote server in the network. While there are good reasons for doing so, a disadvantage of this client-server architecture is clearly that the communication medium may introduce errors, which then impairs speech recognition accuracy. Even sophisticated channel coding cannot completely prevent the occurrence of residual bit errors in the case of temporarily adverse channel conditions, and in packet-oriented transmission packets of data may arrive too late for the given real-time constraints and have to be declared lost. The goal of error concealment is to reduce the detrimental effect that such errors may induce on the recipient of the transmitted speech signal by exploiting residual redundancy in the bit stream at the source coder output. In classical speech transmission a human is the recipient, and erroneous data are reconstructed so as to reduce the subjectively annoying effect of corrupted bits or lost packets. Here, however, a statistical classifier is at the receiving end, which can benefit from knowledge about the quality of the reconstruction. In this book chapter we show how the classical Bayesian decision rule needs to be modified to account for uncertain features, and illustrate how the required feature posterior density can be estimated in the case of distributed speech recognition. Some other techniques for error concealment can be related to this approach. Experimental results are given for both a small and a medium vocabulary recognition task and both for a channel exhibiting bit errors and a packet erasure channel.","lang":"eng"}],"publication":"Automatic Speech Recognition on Mobile Devices and over Communication Networks","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2008/HaIo08.pdf","open_access":"1"}],"series_title":"Advances in Pattern Recognition","language":[{"iso":"eng"}],"date_updated":"2022-01-06T06:51:08Z","title":"Error Concealement","year":"2008","author":[{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"},{"full_name":"Ion, Valentin","last_name":"Ion","first_name":"Valentin"}]},{"date_created":"2019-07-12T05:28:53Z","department":[{"_id":"54"}],"type":"journal_article","keyword":["automatic speech recognition","bit errors","codecs","communication links","corrupted observations","decoding","distributed speech recognition","error-prone communication network","feature vector sequence","hidden Markov model-based ASR","hidden Markov models","inter-frame correlation","Internet telephony","network speech recognition","packet loss","speech posterior","speech recognition","transmission error robust speech recognition","uncertainty decoding","voice-over-IP codecs"],"publication":"IEEE Transactions on Audio, Speech, and Language Processing","issue":"5","abstract":[{"text":"In this paper, we derive an uncertainty decoding rule for automatic speech recognition (ASR), which accounts for both corrupted observations and inter-frame correlation. The conditional independence assumption, prevalent in hidden Markov model-based ASR, is relaxed to obtain a clean speech posterior that is conditioned on the complete observed feature vector sequence. This is a more informative posterior than one conditioned only on the current observation. The novel decoding is used to obtain a transmission-error robust remote ASR system, where the speech capturing unit is connected to the decoder via an error-prone communication network. We show how the clean speech posterior can be computed for communication links being characterized by either bit errors or packet loss. Recognition results are presented for both distributed and network speech recognition, where in the latter case common voice-over-IP codecs are employed.","lang":"eng"}],"language":[{"iso":"eng"}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/IoHa08-1.pdf"}],"doi":"10.1109/TASL.2008.925879","author":[{"first_name":"Valentin","last_name":"Ion","full_name":"Ion, Valentin"},{"id":"242","first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold"}],"title":"A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition","year":"2008","intvolume":"        16","date_updated":"2022-01-06T06:51:10Z","oa":"1","citation":{"mla":"Ion, Valentin, and Reinhold Haeb-Umbach. “A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 16, no. 5, 2008, pp. 1047–60, doi:<a href=\"https://doi.org/10.1109/TASL.2008.925879\">10.1109/TASL.2008.925879</a>.","ama":"Ion V, Haeb-Umbach R. A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>. 2008;16(5):1047-1060. doi:<a href=\"https://doi.org/10.1109/TASL.2008.925879\">10.1109/TASL.2008.925879</a>","bibtex":"@article{Ion_Haeb-Umbach_2008, title={A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition}, volume={16}, DOI={<a href=\"https://doi.org/10.1109/TASL.2008.925879\">10.1109/TASL.2008.925879</a>}, number={5}, journal={IEEE Transactions on Audio, Speech, and Language Processing}, author={Ion, Valentin and Haeb-Umbach, Reinhold}, year={2008}, pages={1047–1060} }","apa":"Ion, V., &#38; Haeb-Umbach, R. (2008). A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition. <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, <i>16</i>(5), 1047–1060. <a href=\"https://doi.org/10.1109/TASL.2008.925879\">https://doi.org/10.1109/TASL.2008.925879</a>","ieee":"V. Ion and R. Haeb-Umbach, “A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition,” <i>IEEE Transactions on Audio, Speech, and Language Processing</i>, vol. 16, no. 5, pp. 1047–1060, 2008.","chicago":"Ion, Valentin, and Reinhold Haeb-Umbach. “A Novel Uncertainty Decoding Rule With Applications to Transmission Error Robust Speech Recognition.” <i>IEEE Transactions on Audio, Speech, and Language Processing</i> 16, no. 5 (2008): 1047–60. <a href=\"https://doi.org/10.1109/TASL.2008.925879\">https://doi.org/10.1109/TASL.2008.925879</a>.","short":"V. Ion, R. Haeb-Umbach, IEEE Transactions on Audio, Speech, and Language Processing 16 (2008) 1047–1060."},"_id":"11820","page":"1047-1060","volume":16,"user_id":"44006","status":"public"},{"publication":"2008 ITG Conference on Voice Communication (SprachKommunikation)","citation":{"chicago":"Ion, Valentin, and Reinhold Haeb-Umbach. “Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition.” <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, 2008, 1–4.","short":"V. Ion, R. Haeb-Umbach, 2008 ITG Conference on Voice Communication (SprachKommunikation) (2008) 1–4.","ieee":"V. Ion and R. Haeb-Umbach, “Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition,” <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, pp. 1–4, 2008.","apa":"Ion, V., &#38; Haeb-Umbach, R. (2008). Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition. <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, 1–4.","bibtex":"@article{Ion_Haeb-Umbach_2008, title={Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition}, journal={2008 ITG Conference on Voice Communication (SprachKommunikation)}, author={Ion, Valentin and Haeb-Umbach, Reinhold}, year={2008}, pages={1–4} }","ama":"Ion V, Haeb-Umbach R. Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition. <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>. 2008:1-4.","mla":"Ion, Valentin, and Reinhold Haeb-Umbach. “Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition.” <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, 2008, pp. 1–4."},"abstract":[{"text":"This paper addresses the robustness of automatic speech recognition to environmental noise. In order to account for reliability of the clean feature estimate we employ the feature posterior density conditioned on observed noisy features to perform uncertainty decoding. We investigate two approaches to estimate the posterior using a discrete feature space, first conditioning only on the current observation, and second on the whole feature sequence of an utterance. Experiments with Aurora 2 showed that the latter provides slightly better performance, as it allows for exploiting the temporal correlations between consecutive features.","lang":"eng"}],"date_created":"2019-07-12T05:28:54Z","type":"journal_article","oa":"1","department":[{"_id":"54"}],"year":"2008","status":"public","title":"Investigations into Uncertainty Decoding Employing a Discrete Feature Space for Noise Robust Automatic Speech Recognition","author":[{"first_name":"Valentin","last_name":"Ion","full_name":"Ion, Valentin"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"date_updated":"2022-01-06T06:51:10Z","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/IoHa08-2.pdf"}],"page":"1-4","_id":"11821","language":[{"iso":"eng"}],"user_id":"44006"},{"date_created":"2019-07-12T05:29:29Z","type":"conference","oa":"1","department":[{"_id":"54"}],"publication":"34. Deutsche Jahrestagung fuer Akustik (DAGA 2008)","citation":{"chicago":"Krueger, Alexander, Ernst Warsitz, and Reinhold Haeb-Umbach. “Blinde Akustische Strahlformung Fuer Anwendungen Im KFZ.” In <i>34. Deutsche Jahrestagung Fuer Akustik (DAGA 2008)</i>, 2008.","short":"A. Krueger, E. Warsitz, R. Haeb-Umbach, in: 34. Deutsche Jahrestagung Fuer Akustik (DAGA 2008), 2008.","ieee":"A. Krueger, E. Warsitz, and R. Haeb-Umbach, “Blinde Akustische Strahlformung fuer Anwendungen im KFZ,” in <i>34. Deutsche Jahrestagung fuer Akustik (DAGA 2008)</i>, 2008.","apa":"Krueger, A., Warsitz, E., &#38; Haeb-Umbach, R. (2008). Blinde Akustische Strahlformung fuer Anwendungen im KFZ. In <i>34. Deutsche Jahrestagung fuer Akustik (DAGA 2008)</i>.","bibtex":"@inproceedings{Krueger_Warsitz_Haeb-Umbach_2008, title={Blinde Akustische Strahlformung fuer Anwendungen im KFZ}, booktitle={34. Deutsche Jahrestagung fuer Akustik (DAGA 2008)}, author={Krueger, Alexander and Warsitz, Ernst and Haeb-Umbach, Reinhold}, year={2008} }","ama":"Krueger A, Warsitz E, Haeb-Umbach R. Blinde Akustische Strahlformung fuer Anwendungen im KFZ. In: <i>34. Deutsche Jahrestagung Fuer Akustik (DAGA 2008)</i>. ; 2008.","mla":"Krueger, Alexander, et al. “Blinde Akustische Strahlformung Fuer Anwendungen Im KFZ.” <i>34. Deutsche Jahrestagung Fuer Akustik (DAGA 2008)</i>, 2008."},"abstract":[{"lang":"eng","text":"In diesem Beitrag werden zwei neuartige akustische Strahlformungsalgorithmen fuer einen Einsatz im KFZ diskutiert. In beiden Verfahren ist fuer jede Frequenzkomponente der Eigenvektor zum groessten Eigenwert eines verallgemeinerten Eigenwertproblems zu bestimmen: bei der einen Varianate stellen die Filterkoeffizienten gerade obigen Eigenvektor dar. Sprachverzerrungen werden mit einem einkanaligen Nachfilter kompensiert. In der anderen Variante, welche die Struktur eines ''Generalized Sidelobe Cancellers'' (GSC) hat, basiert die Blockiermatrix auf obiger Eigenvektorzerlegung."}],"main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/KrWaHa08.pdf"}],"language":[{"iso":"eng"}],"_id":"11851","user_id":"44006","title":"Blinde Akustische Strahlformung fuer Anwendungen im KFZ","status":"public","year":"2008","author":[{"last_name":"Krueger","first_name":"Alexander","full_name":"Krueger, Alexander"},{"first_name":"Ernst","last_name":"Warsitz","full_name":"Warsitz, Ernst"},{"id":"242","last_name":"Haeb-Umbach","first_name":"Reinhold","full_name":"Haeb-Umbach, Reinhold"}],"date_updated":"2022-01-06T06:51:11Z"},{"oa":"1","department":[{"_id":"54"}],"type":"journal_article","date_created":"2019-07-12T05:30:42Z","abstract":[{"lang":"eng","text":"This paper considers the convolutive blind source separation of speech sources in the presence of spatially correlated noise. We introduce a method for estimating the scaled mixing matrix from the sources to the microphones even if coherent noise is present. This is achieved by combining time-frequency sparseness with the generalized eigenvalue decomposition of the power spectral density matrix (PSD) of the noisy speech and noise-only microphone signals. Separation is performed by spatial filtering with coefficients constructed by Gram-Schmidt orthogonalization which places spatial nulls at the interferer{^A}?`s direction. Experimental results show that our approach is capable of separating 2 sources in a reverberant environment (RT60=0ms..500ms) degraded by significant directional noise."}],"citation":{"ieee":"D. H. Tran Vu and R. Haeb-Umbach, “Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming,” <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, pp. 1–4, 2008.","apa":"Tran Vu, D. H., &#38; Haeb-Umbach, R. (2008). Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming. <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, 1–4.","short":"D.H. Tran Vu, R. Haeb-Umbach, 2008 ITG Conference on Voice Communication (SprachKommunikation) (2008) 1–4.","chicago":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming.” <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, 2008, 1–4.","mla":"Tran Vu, Dang Hai, and Reinhold Haeb-Umbach. “Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming.” <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>, 2008, pp. 1–4.","bibtex":"@article{Tran Vu_Haeb-Umbach_2008, title={Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming}, journal={2008 ITG Conference on Voice Communication (SprachKommunikation)}, author={Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}, year={2008}, pages={1–4} }","ama":"Tran Vu DH, Haeb-Umbach R. Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming. <i>2008 ITG Conference on Voice Communication (SprachKommunikation)</i>. 2008:1-4."},"publication":"2008 ITG Conference on Voice Communication (SprachKommunikation)","user_id":"44006","_id":"11914","language":[{"iso":"eng"}],"page":"1-4","main_file_link":[{"url":"https://groups.uni-paderborn.de/nt/pubs/2008/DaHa08.pdf","open_access":"1"}],"date_updated":"2022-01-06T06:51:12Z","author":[{"first_name":"Dang Hai","last_name":"Tran Vu","full_name":"Tran Vu, Dang Hai"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"title":"Blind Speech Separation in Presence of Correlated Noise with Generalized Eigenvector Beamforming","status":"public","year":"2008"},{"date_updated":"2022-01-06T06:51:12Z","title":"Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration","status":"public","year":"2008","author":[{"full_name":"Tran Vu, Dang Hai","first_name":"Dang Hai","last_name":"Tran Vu"},{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"user_id":"44006","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/DaKrHa08.pdf"}],"language":[{"iso":"eng"}],"_id":"11915","abstract":[{"lang":"eng","text":"This Paper deals with a new Technique for multi-channel separation of speech signals from convolutive mixtures under coherent noise. We demonstrate how the scaled transfer functions from the sources to the microphones can be estimated even in the presence of stationary coherent noise. The key to this are generalized eigenvalue decompositions of the power spectral density (PSD) matrices of the noisy speech and noise-only microphone signals with a controlled estimation of these matrices exploiting time-frequency sparseness of the speech sources. Separation is further improved by subsequent Gram-Schmidt orthogonalization which places spatial nulls at the interferers{\\rq} directions, while noise reduction is improved by employing a novel blocking matrix and adaptive interference canceller in a Generalized Sidelobe Canceller (GSC)-like structure. We report promising experimental results for 2 speech sources with significant coherent noise in reverberant environments (RT60=0oms..500ms)."}],"publication":"International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)","citation":{"bibtex":"@inproceedings{Tran Vu_Krueger_Haeb-Umbach_2008, title={Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration}, booktitle={International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)}, author={Tran Vu, Dang Hai and Krueger, Alexander and Haeb-Umbach, Reinhold}, year={2008} }","ama":"Tran Vu DH, Krueger A, Haeb-Umbach R. Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration. In: <i>International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)</i>. ; 2008.","mla":"Tran Vu, Dang Hai, et al. “Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration.” <i>International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)</i>, 2008.","short":"D.H. Tran Vu, A. Krueger, R. Haeb-Umbach, in: International Workshop on Acoustic Echo and Noise Control (IWAENC 2008), 2008.","chicago":"Tran Vu, Dang Hai, Alexander Krueger, and Reinhold Haeb-Umbach. “Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration.” In <i>International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)</i>, 2008.","ieee":"D. H. Tran Vu, A. Krueger, and R. Haeb-Umbach, “Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration,” in <i>International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)</i>, 2008.","apa":"Tran Vu, D. H., Krueger, A., &#38; Haeb-Umbach, R. (2008). Generalized Eigenvector Blind Speech Separation Under Coherent Noise In A GSC Configuration. In <i>International Workshop on Acoustic Echo and Noise Control (IWAENC 2008)</i>."},"type":"conference","department":[{"_id":"54"}],"oa":"1","date_created":"2019-07-12T05:30:43Z"},{"citation":{"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} }","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>","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>.","chicago":"Warsitz, Ernst, Alexander Krueger, and Reinhold Haeb-Umbach. “Speech Enhancement with a New Generalized Eigenvector Blocking Matrix for Application in a Generalized Sidelobe Canceller.” In <i>IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)</i>, 73–76, 2008. <a href=\"https://doi.org/10.1109/ICASSP.2008.4517549\">https://doi.org/10.1109/ICASSP.2008.4517549</a>.","short":"E. Warsitz, A. Krueger, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 73–76.","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.","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>"},"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)","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."}],"date_created":"2019-07-12T05:31:06Z","oa":"1","department":[{"_id":"54"}],"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"],"type":"conference","author":[{"full_name":"Warsitz, Ernst","last_name":"Warsitz","first_name":"Ernst"},{"first_name":"Alexander","last_name":"Krueger","full_name":"Krueger, Alexander"},{"id":"242","full_name":"Haeb-Umbach, Reinhold","last_name":"Haeb-Umbach","first_name":"Reinhold"}],"title":"Speech enhancement with a new generalized eigenvector blocking matrix for application in a generalized sidelobe canceller","year":"2008","status":"public","date_updated":"2022-01-06T06:51:12Z","language":[{"iso":"eng"}],"_id":"11935","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/WaKrHa08.pdf"}],"page":"73-76","doi":"10.1109/ICASSP.2008.4517549","user_id":"44006"},{"page":"4409-4412","main_file_link":[{"open_access":"1","url":"https://groups.uni-paderborn.de/nt/pubs/2008/WiHa08-1.pdf"}],"language":[{"iso":"eng"}],"_id":"11939","doi":"10.1109/ICASSP.2008.4518633","user_id":"44006","year":"2008","status":"public","title":"Modeling the dynamics of speech and noise for speech feature enhancement in ASR","author":[{"full_name":"Windmann, Stefan","first_name":"Stefan","last_name":"Windmann"},{"first_name":"Reinhold","last_name":"Haeb-Umbach","full_name":"Haeb-Umbach, Reinhold","id":"242"}],"date_updated":"2022-01-06T06:51:12Z","date_created":"2019-07-12T05:31:11Z","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"],"type":"conference","oa":"1","department":[{"_id":"54"}],"publication":"IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008)","citation":{"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>.","short":"S. Windmann, R. Haeb-Umbach, in: IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2008), 2008, pp. 4409–4412.","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.","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>","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} }","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>","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>."},"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"}]}]