In different fields of the humanities annotations of multimodal resources are a necessary component of the research workflow. Examples include linguistics, psychology, anthropology, etc. However, creation of those annotations is a very laborious task, which can take 50 to 100 times the length of the annotated media, or more. This can be significantly improved by applying innovative audio and video processing algorithms, which analyze the recordings and provide automated annotations. This is the aim of the AVATecH project, which is a collaboration of the Max Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS. In this paper we present a set of results of automated annotation together with an evaluation of their quality.

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.