Alexander Schmitt

Alexander Schmitt sichtet und analysiert vor dem Hintergrund der j ngsten Reformbestrebungen die Rechnungslegung der Katholischen Kirche in Deutschland. Hierzu ermittelt er zur Beantwortung der Kernfragen innerhalb der kirchlichen Rechnungslegung zun chst ausgehend von der Zwecksetzung eine geeignete Normengrundlage, legt diese aus Sicht der Kirche aus und harmonisiert sie mit den Vorschriften des kanonischen Rechts. Zudem widmet sich die Arbeit speziellen Bilanzierungsproblemen (z.B. Sakralbauten) und weiterf hrenden Fragestellungen der kirchlichen Finanzberichterstattung.

In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use. Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted recordings several thousand real users from commercial and non-commercial SDS.Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer more natural and robust interactions. This work provides insights, lessons and inspiration for future research and development, not only for spoken dialog systems, but for data-driven approaches to human-machine interaction in general.

In Monitoring Adaptive Spoken Dialog Systems, authors Alexander Schmitt and Wolfgang Minker investigate statistical approaches that allow for recognition of negative dialog patterns in Spoken Dialog Systems (SDS). The presented stochastic methods allow a flexible, portable and accurate use. Beginning with the foundations of machine learning and pattern recognition, this monograph examines how frequently users show negative emotions in spoken dialog systems and develop novel approaches to speech-based emotion recognition using hybrid approach to model emotions. The authors make use of statistical methods based on acoustic, linguistic and contextual features to examine the relationship between the interaction flow and the occurrence of emotions using non-acted recordings several thousand real users from commercial and non-commercial SDS.Additionally, the authors present novel statistical methods that spot problems within a dialog based on interaction patterns. The approaches enable future SDS to offer more natural and robust interactions. This work provides insights, lessons and inspiration for future research and development, not only for spoken dialog systems, but for data-driven approaches to human-machine interaction in general.

Auf der Grundlage eines strategischen Bewertungskonzepts fur Geschaftsmodelle in der Logistikdienstleistungsindustrie untersucht Alexander Schmitt die Nachhaltigkeit des 4PL-Providing aus verschiedenen Perspektiven. Er zeigt, dass 4PL-ProvidingTM z.Zt. zwar noch ein geringes Erfolgspotenzial fur Kontraktlogistikdienstleister aufweist, dass diese jedoch wegen ihrer ressourcenbedingten sehr guten Ausgangssituation die eigenen Moglichkeiten eines 4PL-ProvidingTM standig prufen sollten, um rechtzeitig Marktchancen fur ihr Geschaft zu erkennen.