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Towards a Language-independent Intelligibility Assessment of Children with Cleft Lip and Palate
(2009)
We describe a novel evaluation system for the intelligibility assessment of children with CLP on standardized tests. The system is solely based on standard cepstral features in form of MFCCs. No other information like word alignments is used. So the system can be easily adapted to other languages. For each child one GMM is created by adaptation of a UBM to the speaker-specific MFCCs. The components of this GMM are concatenated in order to create a so-called GMM supervector. These GMM supervectors are then used as meta features for an SVR. We evaluated our language-independent system on two different datasets of children suffering from CLP. One dataset contains recordings of 35 German children, where the children named different pictograms. The other dataset contains recordings of 14 Italian speaking children, who repeated standardized sentences. On both datasets we achieved high correlations: up to 0.81 for the German dataset and 0.83 for the Italian dataset.
Time series are series of values ordered by time. This kind of data can be found in many real world settings. Classifying time series is a difficult task and an active area of research. This paper investigates the use of transfer learning in Deep Neural Networks and a 2D representation of time series known as Recurrence Plots. In order to utilize the research done in the area of image classification, where Deep Neural Networks have achieved very good results, we use a Residual Neural Networks architecture known as ResNet. As preprocessing of time series is a major part of every time series classification pipeline, the method proposed simplifies this step and requires only few parameters. For the first time we propose a method for multi time series classification: Training a single network to classify all datasets in the archive with one network. We are among the first to evaluate the method on the latest 2018 release of the UCR archive, a well established time series classification benchmarking dataset.
Ergebnis der Arbeit ist eine interdisziplinäre Zusammenschau zum Erkenntnisobjekt "multimediale Lern- und Masseninformationssysteme" und darauf aufbauend die Vorstellung eines Vorgehensmodell zur Konstruktion dieser Systeme und die Einbettung dieses Modells in ein bestehendes Systemplanungskonzept.
Dazu wird in der Arbeit zunächst der Begriff Multimedia anhand von allgemeinen Kriterien der Mensch-Maschine-Mensch - Kommunikation eingegrenzt und definiert. Ergebnis ist eine Systematik zur Einordnung von wissenschaftlichen Forschungsgebieten in diesem Bereich. Im zweiten Schritt erfolgt eine Untersuchung lerntheoretischer Konzepte anhand eines fünfdimensionalen Rasters. Ergebnis sind zwei Modelle, die sich zur elektronisch unterstützten Wissensvermittlung im allgemeinen eignen. Im dritten Schritt erfolgt eine Auseinandersetzung mit Informationsdarstellungen und Interaktionsmöglichkeiten an der Mensch-Maschine-Schnittstelle. Dazu wird ein konsistentes Raster erarbeitet, anhand dessen wahrnehmungspsychologische und technische Parameter von Informationsdarstellungen und Interaktionsmöglichkeiten untersucht werden. Ergebnis ist die Beschreibung von einem aus der Theater-, Film- und Fernsehbranche adaptierten Prozeß zur Erstellung eines multimedialen Drehbuchs, dem Storyboard. Der vierte Schritt beschreibt die Kombination der lerntheoretischen Konzepte mit dem Prozeß des Storyboardings multimedialer Anwendungen und die Einbettung in ein systemplanerisches Vorgehen dazu. Ergebnis ist ein Phasenkonzept zur Systemplanung multimedialer Lern- und Masseninformationssysteme.
This paper is an interdisciplinary synopsis about multimedia learning systems and mass information systems, and presents an action model for construction of these systems and the embedding of this model in an existing concept of system planning.
First step in the paper is the containment and definition of the term ‘multimedia’ on the basis of general criterions of the human-machine-human communication. Result is a taxonomy to classify scientific research areas in this field.
The second part follows an examination of different concepts of learning theories by means of a five dimensional raster. Output of this examination are two models fitting for computer based learning in general.
The third part discusses information presentation and interaction possibilities at the human - machine - interface. Therefore a consistent raster is acquired, where psychological perception parameters and technical parameters of information presentations and interaction possibilities are examined. This results in the so-called storyboarding, which is the description of a process adapted from theater, film and TV for developing a multimedia script.
The combination of learntheoretical concepts with the process of storyboarding of multimedia applications and the embedding in a system planning action model is described in the fourth part. The result of this last part shows a phase concept for system planning of multimedia learning systems and mass information systems.
In this paper we apply diagnostic analysis to gain a deeper understanding of the performance of the the keyword search system that we have developed for conversational telephone speech in the IARPA Babel program. We summarize the Babel task, its primary performance metric, “actual term weighted value” (ATWV), and our recognition and keyword search systems. Our analysis uses two new oracle ATWV measures, a bootstrap-based ATWV confidence interval, and includes a study of the underpinnings of the large ATWV gains due to system combination. This analysis quantifies the potential ATWV gains from improving the number of true hits and the overall quality of the detection scores in our system's posting lists. It also shows that system combination improves our systems' ATWV via a small increase in the number of true hits in the posting lists.
A growing number of universities and other educational institutions provide recordings of lectures and seminars as an additional resource to the students. In contrast to educational films that are scripted, directed and often shot by film professionals, these plain recordings are typically not post-processed in an editorial sense. Thus, the videos often contain longer periods of inactivity or silence, unnecessary repetitions, or corrections of prior mistakes. This paper describes the FAU Video Lecture Browser system, a web-based platform for the interactive assessment of video lectures, that helps to close the gap between a plain recording and a useful e-learning resource by displaying automatically extracted and ranked key phrases on an augmented time line based on stream graphs. In a pilot study, users of the interface were able to complete a topic localization task about 29 % faster than users provided with the video only while achieving about the same accuracy. The user interactions can be logged on the server to collect data to evaluate the quality of the phrases and rankings, and to train systems that produce customized phrase rankings.
The use of multimedia can significantly improve the quality of case studies, especially with regard to their presentation of reality. The development of multimedia case studies poses a challenge of both a creative and a technical nature. This paper describes the various stages of the development of the case study itself as well as an action model which supports the application of didactical aims in a multimedia case study.
The CALO meeting assistant provides for distributed meeting capture, annotation, automatic transcription and semantic analysis of multiparty meetings, and is part of the larger CALO personal assistant system. This paper summarizes the CALO-MA architecture and its speech recognition and understanding components, which include real-time and offline speech transcription, dialog act segmentation and tagging, question-answer pair identification, action item recognition, decision extraction, and summarization.
The CALO Meeting Assistant (MA) provides for distributed meeting capture, annotation, automatic transcription and semantic analysis of multiparty meetings, and is part of the larger CALO personal assistant system. This paper presents the CALO-MA architecture and its speech recognition and understanding components, which include real-time and offline speech transcription, dialog act segmentation and tagging, topic identification and segmentation, question-answer pair identification, action item recognition, decision extraction, and summarization.
The classical results of the binomial and negative binomial probability distribution are generalized by means of homogeneous Discrete Time Markov Chains to series of stochastically independent random trials. These have not only two possible outcomes but two groups of them -- different kinds of successes and failures with occurrence probabilities depending on the outcome of the previous trial. This generalization allows a uniform view of occupation time, first passage time and recurrence time. Our results are consequently derived and presented in matrix form, the probabilities as well as the moments. They can be applied to all Discrete Time Markov Chains, especially in computer capacity planning, performability and economics.
In earlier studies, we assessed the degree of non-nativeness employing prosodic information. In this paper, we combine prosodic information with (1) features derived from a Gaussian Mixture Model used as Universal Background Model (GMM-UBM), a powerful approach used in speaker identification, and (2) openSMILE, a standard open-source toolkit for extracting acoustic features. We evaluate our approach with English speech from 94 non-native speakers. GMM-UBM or openSMILE modelling alone yields lower performance than our prosodic feature vector; however, adding information from the GMM-UBM modelling or openSMILE by late fusion improves results.
Generating a more detailed understanding of domestic electricity demand is a major topic for energy suppliers and householders in times of climate change.
Over the years there have been many studies on consumption feedback systems to inform householders, disaggregation algorithms for Non-Intrusive-Load-Monitoring (NILM), Real-Time-Pricing (RTP) to promote supply aware behavior through monetary incentives and appliance usage prediction algorithms. While these studies are vital steps towards energy awareness, one of the most fundamental challenges has not yet been tackled: Automated detection of start and stop of usage cycles of household appliances. We argue that most research efforts in this area will benefit from a reliable segmentation method to provide accurate usage information.
We propose a SVM-based segmentation method for home appliances such as dishwashers and washing machines. The method is evaluated using manually annotated electricity measurements of five different appliances recorded over two years in multiple households.
Agenda:
Studienziel Software-Ingenieur(in) Projekte im Rahmen des Informatik-Studiums Projektbeispiele -IT Partner in Forschungsprojekten
Labor für Software-Technik
-IT Partner in Forschungsprojekten -Einzelanfertigungen für genau einen Kunden -Unterstützung von Startups / Testen von Geschäftsideen -Projekte mit kleinen und mittleren Unternehmen Zusammenarbeit mit FH: Nächste Schritte
Stuttering is a complex speech disorder identified by repetitions, prolongations of sounds, syllables or words and blockswhile speaking. Specific stuttering behaviour differs strongly,thus needing personalized therapy. Therapy sessions requirea high level of concentration by the therapist. We introduce STAN, a system to aid speech therapists in stuttering therapysessions. Such an automated feedback system can lower the cognitive load on the therapist and thereby enable a more consistent therapy as well as allowing analysis of stuttering over the span of multiple therapy sessions.
When animals (including humans) first explore a new environment, what they remember is fragmentary knowledge about the places visited. Yet, they have to use such fragmentary knowledge to find their way home.
Humans naturally use more powerful heuristics while lower animals have shown to develop a variety of methods that tend to utilize two key pieces of information, namely distance and orientation information.
Their methods differ depending on how they sense their environment. Could a mobile robot be used to investigate the nature of such a process, commonly referred to in the psychological literature as cognitive mapping? What might be computed in the initial explorations and how is the resulting “cognitive map” be used for localization?
In this paper, we present an approach using a mobile robot to generate a “cognitive map”, the main focus being on experiments conducted in large spaces that the robot cannot apprehend at once due to the very limited range of its sensors. The robot computes a “cognitive map” and uses distance and orientation information for localization.
Das Lehrbuch Software Requirements von Ulrike Hammerschall und Gerd Beneken führt in die Grundkonzepte des Requirements Engineering ein und zeigt anhand vieler anschaulicher Beispiele, wie man systematisch und methodisch bei der Ermittlung, Dokumentation, Spezifikation, Modellierung, Validierung und Verwaltung von Software Requirements vorgeht. Mit seinem Inhalt und didaktisch wertvollem Aufbau richtet sich das Buch an Studierende der Fachrichtung Informatik und Wirtschaftsinformatik, sowie aller verwandten Fachrichtungen, die sich mit den Themen Software Engineering oder Requirements Engineering beschäftigen.
Software Requirements sind die Anforderungen der Anwender an die Funktionalität eines geplanten Software-Systems. Requirements Engineering ist der Prozess zur methodischen Erhebung und Beschreibung der Anforderungen. Die Kunst eines guten Requirements Engineerings ist die Entwicklung einer stabilen Anforderungsbasis als zuverlässige Grundlage für die weitere Entwicklung der Software.
Das vorliegende Buch führt in die Grundkonzepte des Requirements Engineering ein und zeigt anhand vieler Beispiele, wie man systematisch und methodisch bei der Ermittlung, Dokumentation, Spezifikation, Modellierung, Validierung und Verwaltung von Software Requirements vorgeht. Ausführliche Methodenbeschreibungen dienen zur Erläuterung und ein durchgängiges Fallbeispiel hilft dem Leser die Anwendung der Methoden nachzuvollziehen. Mit Hilfe der Übungen am Ende jedes Kapitels, können die Methoden selbst eingeübt werden.
Neben dem klassischen Dokument-getriebenen Requirements Engineering beschäftigt sich das Buch mit den Methoden des agilen Requirements Engineering und vergleicht die beiden Ansätze. Zusätzlich bietet das Buch einen Blick über den Tellerrand und betrachtet die Schnittstellen des Requirements Engineerings zu anderen Teilprozessen im Entwicklungsprozess.
Das Buch richtet sich an Studierende der Fachrichtung Informatik und Wirtschaftsinformatik, sowie aller verwandten Fachrichtungen, die sich mit den Themen Software Engineering oder Requirements Engineering beschäftigen.
- Der RE-Prozess, Vorgehen und Methodik.
- Anforderungsermittlung, -dokumentation und -spezifikation.
- Querschnittliche Aufgaben wie Validierung, Modellierung und Management von Anforderungen
- Agiles RE, Vorgehen und Methodik.
- Schnittstellen zu benachbarten Teilprozessen (Projektmanagement, Qualitätsmanagement, Software-Architektur) sowie zum Usability Engineering.
- Einführung und Verbesserung des Requirements Engineering Prozesses in einer Organisation.
Skriptum Geschäftsprozesse
(2012)
In this article, we describe a semi-automatic calibration algorithm for dereverberation by spectral subtraction. We verify the method by a comparison to a manual calibration derived from measured room impulse responses (RIR). We conduct extensive experiments to understand the effect of all involved parameters and to verify values suggested in the literature. The experiments are performed on a text read by 31 speakers and recorded by a headset and three far-field microphones. Results are measured in terms of automatic speech recognition (ASR) performance using a 1-gram model to emphasize acoustic recognition performance. To accommodate for the acoustic change by dereverberation we apply supervised MAP adaptation to the hidden Markov model output probabilities. The combination of dereverberation and adaptation yields a relative improvement of about 35% in terms of word error rate (WER) compared to the original signal.
This paper presents an approach for applying a dual quaternion hand–eye calibration algorithm on an endoscopic surgery robot. Special focus is on robustness, since the error of position and orientation data provided by the robot can be large depending on the movement actually executed.
Another inherent problem to all hand–eye calibration methods is that non–parallel rotation axes must be used; otherwise, the calibration will fail.
Thus we propose a method for increasing the numerical stability by selecting an optimal set of relative movements from the recorded sequence.
Experimental evaluation shows the error in the estimated transformation when using well–suited and ill–suited data. Additionally, we show how a RANSAC approach can be used for eliminating the erroneous robot data from the selected movements.
In the past decade, semi-continuous hidden Markov models (SCHMMs) have not attracted much attention in the speech recognition community. Growing amounts of training data and increasing sophistication of model estimation led to the impression that continuous HMMs are the best choice of acoustic model. However, recent work on recognition of under-resourced languages faces the same old problem of estimating a large number of parameters from limited amounts of transcribed speech. This has led to a renewed interest in methods of reducing the number of parameters while maintaining or extending the modeling capabilities of continuous models. In this work, we compare classic and multiple-codebook semi-continuous models using diagonal and full covariance matrices with continuous HMMs and subspace Gaussian mixture models. Experiments on the RM and WSJ corpora show that while a classical semicontinuous system does not perform as well as a continuous one, multiple-codebook semi-continuous systems can perform better, particular when using full-covariance Gaussians.
Remeeting is a tool that helps you get more out of in-person
meetings. Calendar integration and a special email address allow
users to email agenda items prior to a certain meeting. A
discrete notification at the time of the meeting reminds the user
to start the recording. During the meeting, the user focuses on the conversation, or can add notes and photos if desired. After the meeting, every participant gets notified by an automated email that lists the participants along with automatically extracted keywords, notes and photos. This stimulates collaboration, and keeps follow-up contributions at a central place: Just reply to add further notes to the meeting. The resulting meeting “document” can be shared with others and reviewed using a web app that acts as a visual index to the meeting. This makes Remeeting the perfect tool for regular group meetings, standups and interviews, where people typically track progress and follow up on. Remeeting is leveraging, promoting and contributing to open source projects including kaldi and docker.
Dieser Beitrag beschreibt, wie Referenzarchitekturen die MDA nutzbar machen. Die Referenzarchitekturen liefern dabei die konzeptionelle Unterstützung für die Konstruktion und Implementierung von Software und die MDA bietet den Rahmen für eine Werkzeugunterstützung. Die praktische Umsetzbarkeit wird mit dem OpenSource Framework AndroMDA und einer Referenzarchitektur der Firma iteratec GmbH gezeigt.
Referenzarchitekturen
(2006)
Die Architektur eines Software-Systems ist im Wesentlichen die Beschreibung des Systems anhand einzelner Beziehungen, die zwischen diesen Bausteinen bestehen. Die Wahl einer bestimmten Architektur ist eine grundlegende Entscheidung im Entwicklungsprozess und hat großen Einfluss auf die Qualität des späteren Systems. In diesem Handbuch wird erstmalig ein fundierter Einstieg und Überblick über den Stand der Technik und zukunftsweisende Entwicklungen im Bereich der Software-Architekturen gegeben. Ausgehend von der Rolle des Software-Architekten werden die Konstruktion und Evolution sowie Migration von Software-Architekturen systematisch aufbereitet. Als Modellierungssprache wird überwiegend die Unified Modeling Language (UML) verwendet. Um ein umfassendes Verständnis für die Bedeutung von Architekturbeschreibungen zu erhalten, werden auch dieThemen Management, Bewertung und Wiederverwendung von Software-Architekturen behandelt. Ebenso wird auf neuere Konzepte wie Model-Driven Architecture (MDA), Software-Produktlinien, Reverse Engineering sowie Performance- und Sicherheitsaspekte eingegangen. Dabei werden die Konzepte beispielhaft illustriert. Im Anhang befinden sich ein Kapitel über formale Grundlagen der Architekturmodellierung, eine Übersicht über Architekturbeschreibungssprachen sowie ein Glossar. Das Buch ist ein Gemeinschaftswerk der Mitglieder des Arbeitskreises Software-Architektur der Gesellschaft für Informatik
Parameter free Non-intrusive Load Monitoring (NILM) algorithms are a major step toward real-world NILM scenarios. The identification of appliances is the key element in NILM. The task consists of identification of the appliance category and its current state. In this paper, we present a param- eter free appliance identification algorithm for NILM using a 2D representation of time series known as unthresholded Recurrence Plots (RP) for appliance category identification. One cycle of voltage and current (V-I trajectory) are transformed into a RP and classified using a Spacial Pyramid Pooling Convolutional Neural Network architecture. The performance of our approach is evaluated on the three public datasets COOLL, PLAID and WHITEDv1.1 and compared to previous publications. We show that compared to other approaches using our architecture no initial parameters have to be manually tuned for each specific dataset.
Wepresentaniterativeregistrationalgorithmfor aligning two differently scaled 3-D point sets. It extends the popular Iterative Closest Point (ICP) algorithm by estimating a scale factor between the two point sets in every iteration.
The presented algorithm is especially useful for the registration of point sets generated by structure-frommotion algorithms, which only reconstruct the 3-D structure of a scene upto scale. LiketheoriginalICPalgorithm,thepresentedalgorithm requires a rough pre-alignment of the point sets.
In order to determine the necessary accuracy of the pre-alignment, wehaveexperimentallyevaluatedthebasinofconvergence of the algorithm with respect to the initial rotation, translation, andscale factor between the two point sets.
We describe an Augmented Reality system using the corners of a color cube for camera calibration. In the augmented image the cube is replaced by a computer generated virtual object.
The cube is localized in an image by the CSC color segmentation algorithm. The camera projection matrix is estimated with a linear method that is followed by a nonlinear refinement step.
Because of possible missclassifications of the segmented color regions and the minimum number of point correspondences used for calibration, the estimated pose of the cube may be very erroneous for some frames; therefore we perform outlier detection and treatment for rendering the virtual object in an acceptable manner.
There are many nearest neighbor algorithms tailor made for ICP,but most of them require Special input data like range Images or triangle meshes.
We focus on efficient nearest neighbor algorithms that do not impose this limitation, and thus can also be used with 3-D point sets generated by structure-frommotion techniques. We shortly present the evaluated algorithms and introduce the modifications we made to improve their efficiency.
In particular, several enhancements to the well-known k-D tree algorithm are described. The first part of our Performance Analysis consists of Experiments on synthetic point sets, whereas the second part features experiments with the ICP algorithm on real point sets. Both parts are completed by a thorough evaluation of the obtained results.
Despite considerable work in automatic meeting summarization over the last few years, comparing results remains difficult due to varied task conditions and evaluations. To address this issue, we present a method for determining the best possible extractive summary given an evaluation metric like ROUGE. Our oracle system is based on a knapsack-packing framework, and though NP-Hard, can be solved nearly optimally by a genetic algorithm. To frame new research results in a meaningful context, we suggest presenting our oracle results alongside two simple baselines. We show oracle and baseline results for a variety of evaluation scenarios that have recently appeared in this field.
In this paper, we present our experience in designing and teaching of our first robotics course for students at primary school level.
The course was carried out over a comparatively short period of time, namely 6 weeks, 2 hours per week. In contrast to many other projects, we use robots that researchers used to conduct their research and discuss problems faced by these researchers. Thus, this is not a behavioural study but a hands-on learning experience for the students.
The aim is to highlight the development of autonomous robots and artificial intelligence as well as to promote science and robotics in schools.
Online Identification of Learner Problem Solving Strategies Using Pattern Recognition Methods
(2010)
Learning and programming environments used in computer science education give feedback to the users by system messages. These are triggered by programming errors and give only "technical" hints without regard to the learners' problem solving process. To adapt the messages not only to the factual but also to the procedural knowledge of the learners, their problem solving strategies have to be identified automatically and in process. This article describes a way to achieve this with the help of pattern recognition methods. Using data from a study with 65 learners aged 12 to 13 using a learning environment for programming, a classification system based on hidden Markov models is trained and integrated in the very same environment. We discuss findings in that data and the performance of the automatic online identification, and present first results using the developed software in class.
We present an Approach for non linea roptimization of the parameters of an endoscopic camera mounted on a surgery robot. The goal is to generate a depth map for each image in order to enhance the quality of medical light fields.
The pose information provided by the robot is used as an initialization, where especially the orientation isi naccurate. Refinement of intrinsic and extrinsic camera parameters is performed by minimizing the back-projectionerror of 3-D points that are reconstructed by triangulation from image Feature stracked over an image sequence.
Optimization of the camera parameters results in an enhancement of Rendering Quality in two ways: More accurate parameters lead to better interpolation as well as to better depth maps for approximating the scenegeometry.
The use of multimedia can significantly improve the quality of case studies, especially with regard to their presentation of reality. The development of multimedia case studies poses a challenge of both a creative and a technical nature. This paper describes the various stages of the development of the case study itself as well as an action model which supports the application of didactical aims in a multimedia case study. This paper then describes experiences with a multimedia case study used at the Department of Information Systems for training students in data processing for business purposes. The report includes a description of how the case study was integrated as a didactic element in a university course, with special emphasis being given to theoretical aspects of presentation and learning. Additionally, a description of the case study and its development rounds off the article. The experiences were gained within the framework of an explorational, empirical study whose results are presented at the end of this paper and form the basis of suggestions for how the case study could be developed further.
This contribution describes experiences with a multimedia case study used at the Department of Information Systems for training students in data processing for business purposes. The report includes a description of how the case study was integrated as a didactic element in a university course, with special emphasis being given to theoretical aspects of presentation and learning. Additionally, a description of the case study and its development rounds off the article. The experiences were gained within the framework of an explorational, empirical study whose results are presented at the end of this paper and form the basis of suggestions for how the case study could be developed further.
The strong technical orientation of the previous multimedia evolution shows a lack of theoretical foundation. Both during the evolution and application of multimedia technology, well-founded theoretical concepts are missing. The intention of this paper is to show categories of different information representations and interaction types and their strengths in representing contents. A classification of multimedia information and interaction types is given also as an
overview of the problem fields of multimedia, especially in the field of learning theory. This classification is used to give some guidelines for using and combining multimedia contents in multimedia systems.
This contribution introduces MOBSY, a fully integrated, autonomous mobile service robot system. It acts as an automatic dialogue-based receptionist for visitors to our institute.
MOBSY incorporates many techniques from different research areas into one working stand-alone system. The techniques involved range from computer vision over speech understanding to classical robotics.
Along with the two main aspects of vision and speech, we also focus on the integration aspect, both on the methodological and on the technical level.
We describe the task and the techniques involved. Finally, we discuss the experiences that we gained with MOBSY during a live performance at our institute.
MOBSY is a fully integrated autonomous mobile service robot system.
It acts as an automatic dialogue based receptionist for visitors of our institute. MOBSY incorporates many techniques from different research areas into one working stand-alone system. Especially the computer vision and dialogue aspects are of main interest from the pattern recognition’s point of view.
To summarize shortly, the involved techniques range from object classification over visual self-localization and recalibration to object tracking with multiple cameras. A dialogue component has to deal with speech recognition, understanding and answer generation. Further techniques needed are navigation, obstacle avoidance, and mechanisms to provide fault tolerant behavior.
This contribution introduces our mobile system MOBSY. Among the main aspects vision and speech, we focus also on the integration aspect, both on the methodological and on the technical level. We describe the task and the involved techniques.
Finally, we discuss the experiences that we gained with MOBSY during a live performance at the 25th anniversary of our institute
Mobility management is a key feature of mobile edge computing. We present an edge cloud infrastructure testbed to explore various mobility scenarios. The design objection of this testbed has been a flexible open platform based on commodity hardware that can easily be scaled with more edge devices and compute resources to perform various edge cloud experiments. As first experiments on our testbed, we have investigated the feasibility of task migration among edge devices caused by edge device overload and unpredictable user movements. We describe the migration process and present some measurements to demonstrate the feasibility.
We present an approach for indoor mapping and localization with a mobile robot using sparse range data, without the need for solving the SLAM problem.
The paper consists of two main parts. First, a split and merge based method for dividing a given metric map into distinct regions is presented, thus creating a topological map in a metric framework.
Spatial information extracted from this map is then used for self-localization. The robot computes local confidence maps for two simple localization strategies based on distance and relative orientation of regions.
The local confidence maps are then fused using an approach adapted from computer vision to produce overall confidence maps. Experiments on data acquired by mobile robots equipped with sonar sensors are presented.
Software-Architektur und Projektmanagement sind Mittel, um große Software-Entwicklungsprojekte beherrschbar zu machen. Die Verbindung zwischen beiden Disziplinen wird in dieser Arbeit mithilfe einer Architekturtheorie hergestellt: Ein Verfahren wird vorgeschlagen, mit dem die Beschreibung der logischen Architektur und die Projektplanung iterativ abgeglichen und verbessert werden können. Verfahren zur architekturbasierten Optimierung der Planung werden daraus entwickelt. Die Dokumentation von Architekturen mithilfe von Architektursichten ist der zweite Schwerpunkt. Mathematisch fundierte Verfahren zur Erzeugung von Sichten werden mithilfe einer Architekturtheorie definiert. Die Verfahren erzeugen etwa Architektursichten, die Projektmanagement und die Kommunikation innerhalb des Projektes mithilfe von Planungsinformationen unterstützen. Ein prototypisches Werkzeug demonstriert Anwendbarkeit der Theorie und der vorgeschlagenen Verfahren
We present an approach for indoor mapping and localisation using sparse range data, acquired by a mobile robot equipped with sonar sensors.
The chapter consists of two main parts. First, a split and merge based method for dividing a given metric map into distinct regions is presented, thus creating a topological map in a metric framework. Spatial information extracted from this map is then used for self-localisation on the return home journey.
The robot computes local confidence maps for two simple localisation strategies based on distance and relative orientation of regions. These local maps are then fused to produce overall confidence maps.
This paper describes the acquisition, transcription and annotation of a multi-media corpus of academic spoken English, the LMELectures. It consists of two lecture se-ries that were read in the summer term 2009 at the com-puter science department of the University of Erlangen-Nuremberg, covering topics in pattern analysis, machine learning and interventional medical image processing. In total, about 40 hours of high-definition audio and video of a single speaker was acquired in a constant recording en-vironment. In addition to the recordings, the presentation slides are available in machine readable (PDF) format. The manual annotations include a suggested segmenta-tion into speech turns and a complete manual transcrip-tion that was done using BLITZSCRIBE2, a new tool for the rapid transcription. For one lecture series, the lecturer assigned key words to each recordings; one recording of that series was further annotated with a list of ranked key phrases by five human annotators each. The corpus is available for non-commercial purpose upon request.
OBJECTIVES:
To generate a fast and robust 3-D visualization of the operation site during minimal invasive surgery.
METHODS:
Light fields are used to model and visualize the 3-D operation site during minimal invasive surgery. An endoscope positioning robot provides the position and orientation of the endoscope. The a priori un-known transformation from the endoscope plug to the endoscope tip (hand-eye transformation) can either be determined by a three-step algorithm, which includes measuring the endoscope length by hand or by using an automatic hand-eye calibration algorithm. Both methods are described in this paper and their respective computation times and accuracies are compared.
RESULTS:
Light fields were generated during real operations and in the laboratory. The comparison of the two methods to determine the unknown hand-eye transformation was done in the laboratory. The results which are being presented in this paper are: rendered images from the generated light fields, the calculated extrinsic camera parameters and their accuracies with respect to the applied hand-eye calibration method, and computation times.
CONCLUSION:
Using an endoscope positioning robot and knowing the hand-eye transformation, the fast and robust generation of light fields for minimal invasive surgery is possible.
Komponenten in J2EE-Patterns
(2002)
In this paper, we describe a new Java framework for an easy and efficient way of developing new GUI based speech processing applications. Standard components are provided to display the speech signal, the power plot, and the spectrogram. Furthermore, a component to create a new transcription and to display and manipulate an existing transcription is provided, as well as a component to display and manually correct external pitch values. These Swing components can be easily embedded into own Java programs. They can be synchronized to display the same region of the speech file. The object-oriented design provides base classes for rapid development of own components.