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Reverberation effects as observed by room microphones severely degrade the performance of automatic speech recognition systems. We investigate the use of dereverberation by spectral subtraction as proposed by Lebart and Boucher and introduce a simple approach to estimate the required decay parameter by clapping hands. Experiments on small vocabulary continuous speech recognition task on read speech show that using the calibrated dereverberation improves WER from 73.2 to 54.7 for the best microphone. In combination with system adaptation, the WER could be reduced to 28.2, which is only a 16% relative loss of performance comparison to using a headset instead of a room microphone.
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.
Die typischerweise gewünschten Einsatzgebiete für Dienstleistungsroboter, z. B. Krankenhäuser oder Seniorenheime, stellen sehr hohe Anforderungen an die Mensch-Maschine-Schnittstelle.
Diese Erfordernisse gehen im Allgemeinen über die Möglichkeiten der Standardsensoren, wie Ultraschalloder Infrarotsensoren, hinaus. Es müssen daher ergänzende Verfahren zum Einsatz kommen.
Aus der Sicht der Mustererkennung sind die Nutzung des Rechnersehens und des natürlichsprachlichen Dialogs von besonderem Interesse. Dieser Beitrag stellt das mobile System MOBS Y vor. MOBS Y ist ein vollkommen integrierter autonomer mobiler Dienstleistungsroboter.
Er dient als ein automatischer dialogbasierter Empfangsservice für Besucher unseres Instituts.
MOBSY vereinigt vielfältige Methoden aus unterschiedlichsten Forschungsgebieten in einem eigenständigen System. Die zum Einsatz kommenden Methoden aus dem Bereich der Bildverarbeitung reichen dabei von Objektklassifikation über visuelle Selbstlokalisierung und Rekalibrierung bis hin zu multiokularer Objektverfolgung.
Die Dialogkomponente umfasst Methoden der Spracherkennung, des Sprachverstehens und die Generierung von Antworten. Im Beitrag werden die zu erfüllende Aufgabe und die einzelnen Verfahren dargestellt.
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
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.
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.
Robust registration of two 3-D point sets is a common problem in computer vision.
The iterative closest point (ICP) algorithm is undoubtedly the most popular algorithm for solving this kind of problem. In this paper, we present the Picky ICP algorithm, which has been created by merging several extensions of the standard ICP algorithm, thus improving its robustness and computation time.
Using pure 3-D point sets as input data, we do not consider additional information like point color or neighborhood relations. In addition to the standard ICP algorithm and the Picky ICP algorithm proposed in this paper, a robust algorithm due to Masuda and Yokoya and the RICP algorithm by Trucco et al. are evaluated.
We have experimentally determined the basin of convergence, robustness to noise and outliers, and computation time of these four ICP based algorithms
Mehrstufige Architekturen mit SQLJ und Enterprise JavaBeans Datenbankanbindung und Erstellung von Komponenten sind ein essentieller Bestandteil von Java-Anwendungen. Bei Java-Schnittstellen rückt der neue ANSI-Standard SQLJ für relationale und objektrelationale Datenbanken immer mehr in den Blickpunkt. Bei mehrstufigen Architekturen ist darüber hinaus die Komponentenbildung unabdingbar, und dabei entwickelt sich EJB zu einem De-facto-Standard. Nach einer grundlegenden Einführung geht es im zweiten Teil des Buches um Java-Schnittstellen zu Datenbanken: JDBC, ODMG und SQLJ8. Wie EJB-Komponenten erstellt werden und auf Java-Datenbanken zugreifen, wird im dritten Teil beschrieben.
We propose a reinforcement learning approach to heating control in home automation, that can acquire a set of rules enabling an agent to heat a room to the desired temperature at a defined time while conserving as much energy as possible. Experimental results are presented that show the feasibility of our method.
The growing size and complexity of software in embedded systems poses new challenges to the safety assessment of embedded control systems. In industrial practice, the control software is mostly treated as a black box during the system's safety analysis. The appropriate representation of the failure propagation of the software is a pressing need in order to increase the accuracy of safety analyses. However, it also increase the effort for creating and maintaining the safety analysis models (such as fault trees) significantly. In this work, we present a method to automatically generate Component Fault Trees from Continuous Function Charts. This method aims at generating the failure propagation model of the detailed software specification. Hence, control software can be included into safety analyses without additional manual effort required to construct the safety analysis models of the software. Moreover, safety analyses created during early system specification phases can be verified by comparing it with the automatically generated one in the detailed specification phased.