@article{11863, abstract = {{In this contribution, a new observation model for the joint compensation of reverberation and noise in the logarithmic mel power spectral density domain will be considered. The proposed observation model relates the noisy reverberant feature to the underlying sequence of clean speech features and the feature of the noise. Nevertheless, due to the complex interaction of these variables in the target domain, the observationmodel cannot be applied to Bayesian feature enhancement directly, calling for approximations that eventually render the observation model useful. The performance of the approximated observation model will highly depend on the capability of modeling the difference between the model and the noisy reverberant observation. A detailed analysis of this observation error will be provided in this work. Among others, it will point out the need to account for the instantaneous ratio of the reverberant speech power and the noise power. Index Terms: Bayesian feature enhancement, observation model for noisy reverberant speech}}, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, journal = {{Speech Communication; 10. ITG Symposium; Proceedings of}}, pages = {{1--4}}, title = {{{Investigations Into a Statistical Observation Model for Logarithmic Mel Power Spectral Density Features of Noisy Reverberant Speech}}}, year = {{2012}}, } @inproceedings{11864, abstract = {{In this work, an observation model for the joint compensation of noise and reverberation in the logarithmic mel power spectral density domain is considered. It relates the features of the noisy reverberant speech to those of the non-reverberant speech and the noise. In contrast to enhancement of features only corrupted by reverberation (reverberant features), enhancement of noisy reverberant features requires a more sophisticated model for the error introduced by the proposed observation model. In a first consideration, it will be shown that this error is highly dependent on the instantaneous ratio of the power of reverberant speech to the power of the noise and, moreover, sensitive to the phase between reverberant speech and noise in the short-time discrete Fourier domain. Afterwards, a statistically motivated approach will be presented allowing for the model of the observation error to be inferred from the error model previously used for the reverberation only case. Finally, the developed observation error model will be utilized in a Bayesian feature enhancement scheme, leading to improvements in word accuracy on the AURORA5 database.}}, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, booktitle = {{Signal Processing, Communications and Computing (ICSPCC), 2012 IEEE International Conference on}}, keywords = {{Robust Automatic Speech Recognition, Bayesian feature enhancement, observation model for reverberant and noisy speech}}, title = {{{A Statistical Observation Model For Noisy Reverberant Speech Features and its Application to Robust ASR}}}, year = {{2012}}, } @techreport{11865, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, title = {{{Derivation of the Power Compensation Constant in the Observation Model for Reverberant Speech in the Logarithmic Mel Power Spectral Domain}}}, year = {{2012}}, } @inproceedings{11910, author = {{Tran Vu, Dang Hai and Haeb-Umbach, Reinhold}}, booktitle = {{International Workshop on Acoustic Signal Enhancement (IWAENC2012)}}, title = {{{Exploiting Temporal Correlations in Joint Multichannel Speech Separation and Noise Suppression using Hidden Markov Models}}}, year = {{2012}}, } @inproceedings{11998, author = {{Eckhoff, D. and Sommer, Christoph and German, R. and Dressler, F.}}, booktitle = {{2011 IEEE Global Telecommunications Conference - GLOBECOM 2011}}, isbn = {{9781424492688}}, title = {{{Cooperative Awareness at Low Vehicle Densities: How Parked Cars Can Help See through Buildings}}}, doi = {{10.1109/glocom.2011.6134402}}, year = {{2012}}, } @inproceedings{12001, author = {{Eckhoff, David and Sommer, Christoph and Dressler, Falko}}, booktitle = {{2012 IEEE 75th Vehicular Technology Conference (VTC Spring)}}, isbn = {{9781467309905}}, title = {{{On the Necessity of Accurate IEEE 802.11P Models for IVC Protocol Simulation}}}, doi = {{10.1109/vetecs.2012.6240064}}, year = {{2012}}, } @inproceedings{12021, author = {{Joerer, Stefan and Dressler, Falko and Sommer, Christoph}}, booktitle = {{Proceedings of the ninth ACM international workshop on Vehicular inter-networking, systems, and applications - VANET '12}}, isbn = {{9781450313179}}, title = {{{Comparing apples and oranges?}}}, doi = {{10.1145/2307888.2307895}}, year = {{2012}}, } @article{12023, author = {{Joerer, Stefan and Sommer, Christoph and Dressler, Falko}}, issn = {{0163-6804}}, journal = {{IEEE Communications Magazine}}, pages = {{82--88}}, title = {{{Toward reproducibility and comparability of IVC simulation studies: a literature survey}}}, doi = {{10.1109/mcom.2012.6316780}}, year = {{2012}}, } @inproceedings{12037, author = {{Malandrino, F. and Casetti, C. and Chiasserini, C. F. and Sommer, Christoph and Dressler, F.}}, booktitle = {{2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC)}}, isbn = {{9781467325691}}, title = {{{Content downloading in vehicular networks: Bringing parked cars into the picture}}}, doi = {{10.1109/pimrc.2012.6362591}}, year = {{2012}}, } @inbook{12895, author = {{Beutner, Marc and Pechuel, R.}}, booktitle = {{Jahrbuch eLearning und Wissensmanagement 2013. Die Zukunft der Bildung und die Rolle der digitalen Medien}}, editor = {{Siepmann, F and Müller, P}}, pages = {{30 -- 34}}, publisher = {{Siepmann Media}}, title = {{{mLearning. Akzeptanz von Mobile Learning. Chancen und Probleme in der betrieblichen Bildung}}}, year = {{2012}}, } @inproceedings{12980, author = {{Cook, Alejandro and Hellebrand, Sybille and E. Imhof, Michael and Mumtaz, Abdullah and Wunderlich, Hans-Joachim}}, booktitle = {{13th IEEE Latin American Test Workshop (LATW'12)}}, pages = {{1--4}}, publisher = {{IEEE}}, title = {{{Built-in Self-Diagnosis Targeting Arbitrary Defects with Partial Pseudo-Exhaustive Test}}}, doi = {{10.1109/latw.2012.6261229}}, year = {{2012}}, } @inproceedings{12981, author = {{Cook, Alejandro and Hellebrand, Sybille and Wunderlich, Hans-Joachim}}, booktitle = {{17th IEEE European Test Symposium (ETS'12)}}, pages = {{1--6}}, publisher = {{IEEE}}, title = {{{Built-in Self-Diagnosis Exploiting Strong Diagnostic Windows in Mixed-Mode Test}}}, doi = {{10.1109/ets.2012.6233025}}, year = {{2012}}, } @inproceedings{15299, author = {{Leinweber, M. and Baumgärtner, L. and Mernberger, M. and Fober, T. and Hüllermeier, Eyke and Klebe, G. and Freisleben, B.}}, booktitle = {{in Proceedings IEEE Conference on Digital Ecosystem Technologies-Complex Environment Engineering Campione d`Italia, Italy}}, title = {{{GPU-based cloud computing for comparing the structure of protein binding sites}}}, year = {{2012}}, } @inbook{15396, author = {{Hüllermeier, Eyke and Fallah Tehrani, A.}}, booktitle = {{Computational Intelligence in Intelligent Data Analysis}}, editor = {{Moewes, C. and Nürnberger, A.}}, pages = {{17--30}}, publisher = {{Springer}}, title = {{{Efficient learning of classifiers based on the 2-additive Choquet integral}}}, year = {{2012}}, } @article{15669, author = {{Schulte, Carsten and Suhonen, Jarkko}}, journal = {{Computer Science Education}}, number = {{2}}, pages = {{79--80}}, title = {{{Koli Calling 2009 and 2010}}}, volume = {{22}}, year = {{2012}}, } @inproceedings{15670, author = {{Schulte, Carsten and Hornung, Malte and Sentance, Sue and Dagiene, Valentina and Jevsikova, Tatjana and Thota, Neena and Eckerdal, Anna and Peters, Anne-Kathrin}}, booktitle = {{Koli Calling}}, pages = {{29--38}}, publisher = {{ACM}}, title = {{{Computer science at school/CS teacher education: Koli working-group report on CS at school}}}, year = {{2012}}, } @inproceedings{15671, author = {{Schulte, Carsten}}, booktitle = {{WiPSCE}}, pages = {{40--47}}, publisher = {{ACM}}, title = {{{Uncovering structure behind function: the experiment as teaching method in computer science education}}}, year = {{2012}}, } @inproceedings{15754, author = {{Bräuning, M. and Hüllermeier, Eyke}}, booktitle = {{In Workshops on Preference Learning at ECAI, European Conference on Artiticial intelligence, Montpellier, France}}, title = {{{Learning conditional lexicographic preference trees}}}, year = {{2012}}, } @inproceedings{15888, author = {{Somorovsky, Juraj and Mayer, Andreas and Schwenk, Jörg and Kampmann, Marco and Jensen, Meiko}}, booktitle = {{Presented as part of the 21st {USENIX} Security Symposium ({USENIX} Security 12)}}, isbn = {{978-931971-95-9}}, pages = {{397--412}}, publisher = {{{USENIX}}}, title = {{{On Breaking SAML: Be Whoever You Want to Be}}}, year = {{2012}}, } @inproceedings{15890, author = {{Somorovsky, Juraj and Schwenk, Jörg}}, booktitle = {{2012 IEEE Eighth World Congress on Services}}, isbn = {{9781467330534}}, title = {{{Technical Analysis of Countermeasures against Attack on XML Encryption -- or -- Just Another Motivation for Authenticated Encryption}}}, doi = {{10.1109/services.2012.6}}, year = {{2012}}, }