Within scientific institutes there exist many language resources. These resources are often quite specialized and relatively unknown. The current infrastructural initiatives try to tackle this issue by collecting metadata about the resources and establishing centers with stable repositories to ensure the availability of the resources. It would be beneficial if the researcher could, by means of a simple query, determine which resources and which centers contain information useful to his or her research, or even work on a set of distributed resources as a virtual corpus. In this article we propose an architecture for a distributed search environment allowing researchers to perform searches in a set of distributed language resources.

Annotation of digital recordings in humanities research still is, to a large extend, a process that is performed manually. This paper describes the first pattern recognition based software components developed in the AVATecH project and their integration in the annotation tool ELAN. AVATecH (Advancing Video/Audio Technology in Humanities Research) is a project that involves two Max Planck Institutes (Max Planck Institute for Psycholinguistics, Nijmegen, Max Planck Institute for Social Anthropology, Halle) and two Fraunhofer Institutes (Fraunhofer-Institut für Intelligente Analyse- und Informationssysteme IAIS, Sankt Augustin, Fraunhofer Heinrich-Hertz-Institute, Berlin) and that aims to develop and implement audio and video technology for semi-automatic annotation of heterogeneous media collections as they occur in multimedia based research. The highly diverse nature of the digital recordings stored in the archives of both Max Planck Institutes, poses a huge challenge to most of the existing pattern recognition solutions and is a motivation to make such technology available to researchers in the humanities.