@inproceedings{11816, abstract = {{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.}}, author = {{Hoang, Manh Kha and Haeb-Umbach, Reinhold}}, booktitle = {{38th International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2013)}}, issn = {{1520-6149}}, keywords = {{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}}, pages = {{3721--3725}}, title = {{{Parameter estimation and classification of censored Gaussian data with application to WiFi indoor positioning}}}, doi = {{10.1109/ICASSP.2013.6638353}}, year = {{2013}}, } @article{11862, abstract = {{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.}}, author = {{Leutnant, Volker and Krueger, Alexander and Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Audio, Speech, and Language Processing}}, keywords = {{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}}, number = {{8}}, pages = {{1640--1652}}, title = {{{Bayesian Feature Enhancement for Reverberation and Noise Robust Speech Recognition}}}, doi = {{10.1109/TASL.2013.2258013}}, volume = {{21}}, year = {{2013}}, } @inproceedings{36994, abstract = {{This paper proposes a quality driven, simulation based approach to functional design verification, which applies mainly to IP-level HDL designs with well specified test instruction format and is evaluated on a soft microprocessor core MB-LITE [5]. The approach utilizes mutation analysis as the quality metric to steer an automated simulation data generation process. It leads to a simulation flow with two phases towards an enhanced mutation analysis result. First in a random simulation phase, an in-loop heuristics is deployed and adjusts dynamically the test probability distribution so as to improve the coverage efficiency. Next, for each remaining hard-to-kill mutant, a search heuristics on test input space is developed to iteratively locate a target test, using a specific objective cost function for the goal of killing HDL mutant. The effectiveness of this integrated two-phase simulation flow is demonstrated by the results with the MB-LITE microprocessor IP.}}, author = {{Xie, Tao and Müller, Wolfgang and Letombe, Florian}}, booktitle = {{Proceedings of SOCC2012}}, keywords = {{Analytical models, Hardware design languages, Microprocessors, Cost function, Data models, Search problems, IP networks}}, publisher = {{IEEE}}, title = {{{Mutation-Analysis Driven Functional Verification of a Soft Microprocessor}}}, doi = {{10.1109/SOCC.2012.6398362}}, year = {{2012}}, } @inproceedings{37002, abstract = {{HDL-mutation based fault injection and analysis is considered as an important coverage metric for measuring the quality of design simulation processes [20, 3, 1, 2]. In this work, we try to solve the problem of automatic simulation data generation targeting HDL mutation faults. We follow a search based approach and eliminate the need for symbolic execution and mathematical constraint solving from existing work. An objective cost function is defined on the test input space and serves the guidance of search for fault-detecting test data. This is done by first mapping the simulation traces under a test onto a control and data flow graph structure which is extracted from the design. Then the progress of fault detection can be measured quantitatively on this graph to be the cost value. By minimizing this cost we approach the target test data. The effectiveness of the cost function is investigated under an example neighborhood search scheme. Case study with a floating point arithmetic IP design has shown that the cost function is able to guide effectively the search procedure towards a fault-detecting test. The cost calculation time as the search overhead was also observed to be minor compared to the actual design simulation time.}}, author = {{Xie, Tao and Müller, Wolfgang and Letombe, Florian}}, booktitle = {{Proceedings of Euromicro DSD 2011}}, isbn = {{978-1-4577-1048-3}}, keywords = {{Hardware design languages, Cost function, Computational modeling, Fault detection, Data models, Analytical models, Testing}}, publisher = {{IEEE}}, title = {{{HDL-Mutation Based Simulation Data Generation by Propagation Guided Search}}}, doi = {{10.1109/DSD.2011.83}}, year = {{2011}}, } @article{11892, abstract = {{For an environment to be perceived as being smart, contextual information has to be gathered to adapt the system's behavior and its interface towards the user. Being a rich source of context information speech can be acquired unobtrusively by microphone arrays and then processed to extract information about the user and his environment. In this paper, a system for joint temporal segmentation, speaker localization, and identification is presented, which is supported by face identification from video data obtained from a steerable camera. Special attention is paid to latency aspects and online processing capabilities, as they are important for the application under investigation, namely ambient communication. It describes the vision of terminal-less, session-less and multi-modal telecommunication with remote partners, where the user can move freely within his home while the communication follows him. The speaker diarization serves as a context source, which has been integrated in a service-oriented middleware architecture and provided to the application to select the most appropriate I/O device and to steer the camera towards the speaker during ambient communication.}}, author = {{Schmalenstroeer, Joerg and Haeb-Umbach, Reinhold}}, journal = {{IEEE Journal of Selected Topics in Signal Processing}}, keywords = {{audio streaming, audio visual data streaming, context information speech, face identification, face recognition, image segmentation, middleware, multimodal telecommunication, online diarization, service oriented middleware architecture, sessionless telecommunication, software architecture, speaker identification, speaker localization, speaker recognition, steerable camera, telecommunication computing, temporal segmentation, terminal-less telecommunication, video streaming}}, number = {{5}}, pages = {{845--856}}, title = {{{Online Diarization of Streaming Audio-Visual Data for Smart Environments}}}, doi = {{10.1109/JSTSP.2010.2050519}}, volume = {{4}}, year = {{2010}}, } @inproceedings{37050, abstract = {{The main obstacle for the wide acceptance of UML and SysML in the design of electronic systems is due to a major gap in the design flow between UML-based modeling and SystemC-based verification. To overcome this gap, we present an approach developed in the SATURN project which introduces UML profiles for the co-modeling of SystemC and C with code generation support in the context of the SysML tool suite ARTiSAN Studio®. We finally discuss the evaluation of the approach by two case studies.}}, author = {{Müller, Wolfgang and He, Da and Mischkalla, Fabian and Wegele, Arthur and Larkham, Adrian and Whiston, Paul and Penil, Pablo and Villar, Eugenio and Mitas, Nikolaos and Kritharidis, Dimitros and Azcarate, Florent and Carballeda, Manuel}}, booktitle = {{Proceedings of the IEEE Computer Society Annual Symposium on VLSI}}, keywords = {{Communicate Sequential Process Virtual Platform Smart Camera Synchronous Data Flow Artisan Studio}}, title = {{{The SATURN Approach to SysML-based HW/SW Codesign}}}, doi = {{10.1007/978-94-007-1488-5_9}}, year = {{2010}}, } @inproceedings{11943, abstract = {{A marginalized particle filter is proposed for performing single channel speech enhancement with a non-linear dynamic state model. The system consists of a particle filter for tracking line spectral pair (LSP) parameters and a Kalman filter per particle for speech enhancement. The state model for the LSPs has been learnt on clean speech training data. In our approach parameters and speech samples are processed at different time scales by assuming the parameters to be constant for small blocks of data. Further enhancement is obtained by an iteration which can be applied on these small blocks. The experiments show that similar SNR gains are obtained as with the Kalman-LM-iterative algorithm. However better values of the noise level and the log-spectral distance are achieved}}, author = {{Windmann, Stefan and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2006)}}, keywords = {{clean speech training data, iterative methods, iterative speech enhancement, Kalman filter, Kalman filters, Kalman-LM-iterative algorithm, line spectral pair parameters, log-spectral distance, marginalized particle filter, noise level, nonlinear dynamic state speech model, particle filtering (numerical methods), single channel speech enhancement, SNR gains, speech enhancement, speech samples}}, pages = {{I}}, title = {{{Iterative Speech Enhancement using a Non-Linear Dynamic State Model of Speech and its Parameters}}}, doi = {{10.1109/ICASSP.2006.1660058}}, volume = {{1}}, year = {{2006}}, } @inproceedings{39050, abstract = {{Currently, middleware for smart home networks with embedded and mobile devices are in the focus of several investigations. In this paper, we propose a middleware for secure management of device and user profiles by integrating a profile database with a generic authentication scheme for an X.509 enabled ticket management in the context of the OSGi framework. After the introduction of the individual system components and their interaction, we also discuss potential system attacks.}}, author = {{Ziegler, Max and Müller, Wolfgang and Schäfer, Robbie and Loeser, Chris}}, booktitle = {{Proceedings of the 1st International Workshop on Secure and Ubiquitous Networks (SUN-2005)}}, isbn = {{0-7695-2424-9}}, keywords = {{Intelligent networks, Smart homes, Middleware, Project management, Data security, Ubiquitous computing, Context-aware services, Computer architecture, Home automation, Environmental management}}, location = {{Copenhagen, Denmark }}, publisher = {{IEEE}}, title = {{{Secure Profile Management in Smart Home Networks}}}, doi = {{10.1109/DEXA.2005.171}}, year = {{2005}}, } @inproceedings{39052, abstract = {{Smart homes provide their users with maximum comfort and convenience. In this paper, we present a profile management framework for situation-dependent customization in smart home environments, which meet the user preferences with given device capabilities. We apply profile processing and evolution methods to customize profiles on the fly and to automatically evolve user preferences. Furthermore, we give a comprehensive study on profile management technology.}}, author = {{Groppe, Jinghua and Müller, Wolfgang}}, booktitle = {{Proceedings of the 1st International Workshop on Secure and Ubiquitous Networks (SUN-2005)}}, isbn = {{0-7695-2424-9}}, keywords = {{Technology management, Smart homes, Environmental management, Resource description framework, Data models, Navigation, Mobile computing, Embedded computing, Ubiquitous computing, Mobile communication}}, location = {{Copenhagen, Denmark }}, publisher = {{IEEE}}, title = {{{Profile Management technology for Smart Customization in Private Home Applications}}}, doi = {{10.1109/DEXA.2005.156}}, year = {{2005}}, } @inproceedings{39061, abstract = {{This article presents an approach, which combines theorem proving-based refinement with model checking for state based real-time systems. Our verification flow starts from UML state diagrams, which are translated to the formal B language and are model checked for real-time properties. By means of the B language and a B theorem prover, refined state diagrams are verified against their abstract representation. The approach is presented by means of the refinement of a digital echo cancellation unit.}}, author = {{Krupp, Alexander and Müller, Wolfgang and Oliver, Ian}}, booktitle = {{Proceedings of DATE’04 Designers' Forum}}, isbn = {{0-7695-2085-5}}, keywords = {{Echo cancellers, Logic, Unified modeling language, Automata, Data structures, Boolean functions, Electronic design automation and methodology, Prototypes, Specification languages, Constraint theory}}, title = {{{Formal Refinement and Model Checking of An Echo Cancellation Unit}}}, doi = {{10.1109/DATE.2004.1269214}}, year = {{2004}}, } @article{11778, abstract = {{In this paper, it is shown that a correlation criterion is the appropriate criterion for bottom-up clustering to obtain broad phonetic class regression trees for maximum likelihood linear regression (MLLR)-based speaker adaptation. The correlation structure among speech units is estimated on the speaker-independent training data. In adaptation experiments the tree outperformed a regression tree obtained from clustering according to closeness in acoustic space and achieved results comparable with those of a manually designed broad phonetic class tree}}, author = {{Haeb-Umbach, Reinhold}}, journal = {{IEEE Transactions on Speech and Audio Processing}}, keywords = {{acoustic space, adaptation experiments, automatic generation, bottom-up clustering, broad phonetic class regression trees, correlation criterion, correlation methods, maximum likelihood estimation, maximum likelihood linear regression based speaker adaptation, MLLR adaptation, pattern clustering, phonetic regression class trees, speaker-independent training data, speech recognition, speech units, statistical analysis, trees (mathematics)}}, number = {{3}}, pages = {{299--302}}, title = {{{Automatic generation of phonetic regression class trees for MLLR adaptation}}}, doi = {{10.1109/89.906003}}, volume = {{9}}, year = {{2001}}, } @inproceedings{11869, abstract = {{Amongst several data driven approaches for designing filters for the time sequence of spectral parameters, the linear discriminant analysis (LDA) based method has been proposed for automatic speech recognition. Here we apply LDA-based filter design to cepstral features, which better match the inherent assumption of this method that feature vector components are uncorrelated. Extensive recognition experiments have been conducted both on the standard TIMIT phone recognition task and on a proprietary 130-words command word task under various adverse environmental conditions, including reverberant data with real-life room impulse responses and data processed by acoustic echo cancellation algorithms. Significant error rate reductions have been achieved when applying the novel long-range feature filters compared to standard approaches employing cepstral mean normalization and delta and delta-delta features, in particular when facing acoustic echo cancellation scenarios and room reverberation. For example, the phone accuracy on reverberated TIMIT data could be increased from 50.7\% to 56.0\%}}, author = {{Lieb, M. and Haeb-Umbach, Reinhold}}, booktitle = {{IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2000)}}, keywords = {{acoustic echo cancellation algorithms, adverse environmental conditions, automatic speech recognition, cepstral analysis, cepstral features, cepstral mean normalization, command word task, delta-delta features, delta features, echo suppression, error rate reductions, feature vector components, FIR filters, LDA derived cepstral trajectory filters, linear discriminant analysis, long-range feature filters, phone accuracy, real-life room impulse responses, reverberant data, spectral parameters, speech recognition, standard TIMIT phone recognition task}}, pages = {{II1105--II1108 vol.2}}, title = {{{LDA derived cepstral trajectory filters in adverse environmental conditions}}}, doi = {{10.1109/ICASSP.2000.859157}}, volume = {{2}}, year = {{2000}}, }