Franz Rosenzweig. Der Stern der Erlösung

Den Konflikt zwischen Modernität und jüdisch-orthodoxer Glaubenspraxis trug Franz Rosenzweig auf seine ganz eigene Art aus. Die Bewegung führt dramatisch von der noblen Peripherie in das Zentrum jüdischen Lebens und dessen Lehr- und Glaubenspraxis. Für das Werk von Emmanuel Levinas stellt Franz Rosenzweig wohl die wichtigste Referenz dar. "Mit ihrem „messianischen“ Zeitkonzept ist die jüdische Religion den Erfahrungsreligionen näher als das Christentum. Das Judentum, so schreibt Karlheinz Kleinbach in seinem Portrait des jüdischen Philosophen Franz Rosenzweig, „lebt innerweltlich in der Gegenwärtigkeit. Liturgie und Ritus stehen nicht im Gegensatz zum alltäglichen Leben, sondern sind vielmehr dessen Existenzmodus.“ Mensch und Gott und Welt sind für Rosenzweig nicht zu verbindende Elemente. Nur in der Gemeinschaft, im Gespräch wird es möglich, das trennende „Und“ zu überbrücken" (Reusch)

Assessment of Speech Dialog Systems using Multi-Modal Cognitive Load Analysis and Driving Performance Metrics

In this paper, cognitive load analysis via acoustic- and CAN-Bus-based driver performance metrics is employed to assess two different commercial speech dialog systems (SDS) during in-vehicle use. Several metrics are proposed to measure increases in stress, distraction and cognitive load and we compare these measures with statistical analysis of the speech recognition component of each SDS. It is found that care must be taken when designing an SDS as it may increase cognitive load which can be observed through increased speech response delay (SRD), changes in speech production due to negative emotion towards the SDS, and decreased driving performance on lateral control tasks. From this study, guidelines are presented for designing systems which are to be used in vehicular environments.

A Likelihood-Maximizing Framework for Enhanced In-Car Speech Recognition Based on Speech Dialog System Interaction

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating noncritical in-car systems. Under such conditions, however, speech recognition accuracy degrades significantly, and techniques such as speech enhancement are required to improve these accuracies. Likelihood-maximizing (LIMA) frameworks optimize speech enhancement algorithms based on recognized state sequences rather than traditional signal-level criteria such as maximizing signal-to-noise ratio. LIMA frameworks typically require calibration utterances to generate optimized enhancement parameters that are used for all subsequent utterances. Under such a scheme, suboptimal recognition performance occurs in noise conditions that are significantly different from that present during the calibration session – a serious problem in rapidly changing noise environments out on the open road. In this chapter, we propose a dialog-based design that allows regular optimization iterations in order to track the ever-changing noise conditions. Experiments using Mel-filterbank noise subtraction (MFNS) are performed to determine the optimization requirements for vehicular environments and show that minimal optimization is required to improve speech recognition, avoid over-optimization, and ultimately assist with semireal-time operation. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session only.

Dorothea (Dola) Guttmann (seated second from right) with other members of Sport Reichsbund jüdischer Frontsoldaten (RjF) Tilsit Portraits Groups

Verso: handwritten list of names

Membership cards of Judith Rosenthal, Elma Rosenthal and Arthur Rosenthal to the Jüdischer Kulturbund Berlin Portraits Family

Digital Image

Dialog

This work, commissioned by Campbelltown Arts Centre, was created as part of an online residency in Western Sydney. The residency took the form of an online survey of students in Western Sydney schools that queried participants on their favourite moments, characters and dialogue from film and television. Using this information as a starting point, the work used appropriated footage to weave together a 6-way cross-screen conversation. Spouting occasionally recognizable phrases that then devolve into meaningless cliché, the narrative content of this fragmented back-and-forth hovers somewhere in between familiarity and non-sense.