16829900
A Robust Speaking Face Modelling Approach Based on Multilevel Fusion
approach based on multilevel fusion of 3D face biometric information with audio and visual speech information for biometric identity verification applications. The proposed approach combines the information from three audio-video based modules, namely: audio, visual speech, and 3D face and performs tri-module fusion in an automatic, unsupervised and adaptive manner, by adapting to the local performance of each module. This is done by taking the output-score based reliability estimates (confidence measures) of each of the module into account. The module weightings are determined automatically such that the reliability measure of the combined scores is maximised. To test the robustness of the proposed approach, the audio and visual speech (mouth) modalities are degraded to emulate various levels of train/test mismatch; employing additive white Gaussian noise for the audio and JPEG compression for the video signals. The results show improved fusion performance for a range of tested levels of audio and video degradation, compared to the individual module performances. Experiments on a 3D stereovision database AVOZES show that, at severe levels of audio and video mismatch, the audio, mouth, 3D face, and tri-module (audio+mouth+3D face) fusion EERs were 42.9%, 32%, 15%, and 7.3% respectively for biometric speaker identity verification application. I.
5705405
Robust face-voice based speaker identity verification using multilevel fusion
In this paper, we propose a robust multilevel fusion strategy involving cascaded multimodal fusion of audio-lip-face motion, correlation and depth features for biometric person authentication. The proposed approach combines the information from different audio-video based modules, namely: audio-lip motion module, audio-lip correlation module, 2D+3D motion-depth fusion module, and performs a hybrid cascaded fusion in an automatic, unsupervised and adaptive manner, by adapting to the local performance of each module. This is done by taking the output-score based reliability estimates (confidence measures) of each of the module into account. The module weightings are determined automatically such that the reliability measure of the combined scores is maximised. To test the robustness of the proposed approach, the audio and visual speech (mouth) modalities are degraded to emulate various levels of train/test mismatch; employing additive white Gaussian noise for the audio and JPEG compression for the video signals. The results show improved fusion performance for a range of tested levels of audio and video degradation, compared to the individual module performances. Experiments on a 3D stereovision database AVOZES show that, at severe levels of audio and video mismatch, the audio, mouth, 3D face, and tri-module (audio-lip motion, correlation and depth) fusion EERs were 42.9%, 32%, 15%, and 7.3%, respectively, for biometric person authentication task.
43139712
Speaker Verification with Fuzzy Fusion and Genetic Optimization
25044094
Generalised Fuzzy Hidden Markov Models for Speech Recognition
A generalised fuzzy approach to statistical modelling techniques for speech recognition is proposed in this paper. Fuzzy C-means (FCM) and fuzzy entropy (FE) techniques are combined into a generalised fuzzy technique and applied to hidden Markov models (HMMs). A more robust version of the above fuzzy technique based on the noise clustering (NC) method is also proposed. Experimental results were performed on the TI46 speech data corpus. A significant result for isolatedword recognition performed on a highly confusable vocabulary consisting of the nine English E-set words is that, a 33.8% recognition error rate for the HMM-based system was reduced to 30.5%, 29.9%, 29.8% and 27.8%, respectively, by using the FCM-HMM, the FE-HMM, the NC-FE-HMM, and the NC-FCM-HMM-based systems.
987011
Similarity normalization for speaker verification by fuzzy fusion
Abstract Similarity or likelihood normalization techniques are important for speaker verification systems as they help to alleviate the variations in the speech signals. In the conventional normalization, the a priori probabilities of the cohort speakers are assumed to be equal. From this standpoint, we apply the theory of fuzzy measure and fuzzy integral to combine the likelihood values of the cohort speakers in which the assumption of equal a priori probabilities is relaxed. This approach replaces the conventional normalization term by the fuzzy integral which acts as a non-linear fusion of the similarity measures of an utterance assigned to the cohort speakers. We illustrate the performance of the proposed approach by testing the speaker verification system with both the conventional and the fuzzy algorithms using the commercial speech corpus TI46. The results in terms of the equal error rates show that the speaker verification system using the fuzzy integral is more flexible and more favorable than the conventional normalization method.
35465720
Reliability score based multimodal fusion for biometric person authentication
In this paper, we propose a robust multilevel fusion strategy involving cascaded fusion of hybrid multimodal fusion of audio-lip-face motion, correlation and depth features for biometric person authentication. The proposed approach combines the information from different audio-video based modules, namely: audio-lip motion module, audio-lip correlation module, 2D+3D motiondepth fusion module, and performs a hybrid cascaded fusion in an automatic, unsupervised and adaptive manner, by adapting to the local performance of each module. This is done by taking the output-score based reliability estimates (confidence measures) of each of the module into account. The module weightings are determined automatically such that the reliability measure of the combined scores is maximised. To test the robustness of the proposed approach, the audio and visual speech (mouth) modalities are degraded to emulate various levels of train/test mismatch; employing additive white Gaussian noise for the audio and JPEG compression for the video signals. The results show improved fusion performance for a range of tested levels of audio and video degradation, compared to the individual module performances. Experiments on a 3D stereovision database AVOZES show that, at severe levels of audio and video mismatch, the audio, mouth, 3D face, and tri-module (audio-lip motion, correlation and depth) fusion EERs were 42.9%, 32%, 15%, and 7.3% respectively for biometric person authentication task.
42894925
Modeling of Context-Aware Self-Adaptive Applications in Ubiquitous and Service-Oriented Environments
Mobile computing in ubiquitous environments has to cope with both predictable and unpredictable changes in the execution context, which introduces the need for context-aware adaptive applications. Such environments are also characterized by dynamically discoverable services that can be utilized by applications to improve their functionality and quality of service (QoS). Thus, application adaptation decisions not only depend on context properties, but also on service availability and QoS-properties. In this chapter we present a novel comprehensive modeling approach that facilitates the model-driven development of such applications. Our focus is on modeling concepts which align the description of services and their QoS-properties with the context modeling approach. We provide a harmonized view on context and service properties, bridging the syntactical and semantic differences through an ontology. We also consider related aspects like semantic service discovery and service level agreements.
32510848
Using Augmented Virtuality for Remote Collaboration
This paper describes the concept, prototypical implementation, and usability evaluation of the Augmented Virtuality (AV)-based videoconferencing (VC) system cAR/PE!. We present a solution that allows three participants at different locations to communicate over a network in an environment simulating a traditional face-to-face meeting. Integrated into the AV environment are live video streams of the participants spatially arranged around a virtual table, a large virtual presentation screen for 2D display and application sharing, and 3D geometry (models) within the room and on top of the table. We describe the general concept and application scenario as well as the actual hardware setup, the implementation, and the use of the system in its current state. Results of two usability studies with 87 subjects are presented that show the general usability of our approach as well as good overall satisfaction. Parts of the work described here were presented as a poster at the second International Symposium on Mixed and Augmented Reality (Regenbrecht, Ott, Wagner, Lum, Kohler, et al., 2003. An Augmented Virtuality Approach to 3D Videoconferencing. Poster at 2nd Int. Symp. on Mixed and Aug. Reality, Tokyo.).
209498655
Preface
The title of this book ‘One-Dimensional Finite Elements: An Introduction to the FE Method’ stands for content and focus. Nowadays, much literature regarding the topic of the finite element method exists. The different works reflect the multifaceted perceptions and application possibilities. The basic idea of this introduction into the finite element method relies on the concept of explaining the complex method with the help of one-dimensional elements. It is the goal to introduce the manifold aspects of the finite element method and to enable the reader to get a methodical understanding of important subject areas. The reader learns to understand the assumptions and derivations at different physical problems in structural mechanics. Furthermore, he/she learns to critically evaluate possibilities and limitations of the finite element method. Additional comprehensive mathematical descriptions, which solely result from advanced illustrations for twoor three-dimensional problems, are omitted. Hence, the mathematical description largely remains simple and clear. The focus on one-dimensional elements, however, is not just a pure limitation on a simpler and clearer formal illustration of the necessary equations. Within structural engineering, there are various structures— for example bridges or high transmission towers—which are usually modeled via one-dimensional elements. Therefore, this work also contains a ‘set of tools’, which can also be applied in practice. The concentration on one-dimensional elements is new for a textbook and allows the treatment of various basic and demanding physical questions of structural mechanics within one single textbook. This new concept, therefore, allows a methodical understanding of important subject areas (for example plasticity or composite materials), which occur to a prospective engineer during professional work, which however are seldom treated in this way at universities. Consequently, simple access is possible, also in supplementary areas of application of the finite element method. This book originates from a collection of lecture notes which were developed as written material for lectures and training documents for specialized courses on the finite element method. Especially, the calculated examples and the supplementary
751960
Performance Evaluation Methodologies for Abstract Data Type Implementation Techniques
Abstract The runtime management system for a programming language must allow the efficient manipulation of complex objects, such as instances of abstract data types (ADTs). We describe an implementation model for ADTs based on coroutine objects (i.e. as an alternative to ad hoc modifications of the runtime stack). We evaluate the performances of variants of our implementation model using two different approaches: a benchmarking technique which monitors actual costs for test programs and a “pseudo-execution” technique which estimates costs based on idealized instruction timings. The results of our comparison indicate that the two forms of evaluation give very similar cost estimates, supporting the use of the (cheaper) pseudo-execution technique. The overall performance results identify applications in which our coroutine implementation model has definite strengths and weaknesses. Finally, our implementation approach is compared with modified stack implementations used in other ADT systems.
10411388
Large-scale linear programming techniques for the design of protein folding potentials
Abstract.We present large-scale optimization techniques to model the energy function that underlies the folding process of proteins. Linear Programming is used to identify parameters in the energy function model, the objective being that the model predict the structure of known proteins correctly. Such trained functions can then be used either for ab-initio prediction or for recognition of unknown structures. In order to obtain good energy models we need to be able to solve dense Linear Programming Problems with tens (possibly hundreds) of millions of constraints in a few hundred parameters, which we achieve by tailoring and parallelizing the interior-point code PCx.