Sebastian Tschöpel

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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(More)
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(More)
The AXES project participated in the interactive known-item search task (KIS) and the interactive instance search task (INS) for TRECVid 2011. We used the same system architecture and a nearly identical user interface for both the KIS and INS tasks. Both systems made use of text search on ASR, visual concept detectors, and visual similarity search. The user(More)
The Fraunhofer IAIS AudioMining system for vocabulary independent spoken term detection is able to provide automatic speech recognition (ASR) transcripts for audio-visual data. These transcripts can be used to search for information, e.g., in audio-visual archives. We experienced difficulties in the process of browsing for desired content when only these(More)
In the AVATecH project the Max-Planck Institute for Psycholinguistics (MPI) and the Fraunhofer institutes HHI and IAIS aim to significantly speed up the process of creating annotations of audio-visual data for humanities research. For this we integrate state-of-theart audio and video pattern recognition algorithms into the widely used ELAN annotation tool.(More)
We describe a novel system which simplifies recommendation of video scenes in social networks, thereby attracting a new audience for existing video portals. Users can select interesting quotes from a speech recognition transcript, and share the corresponding video scene with their social circle with minimal effort. The system has been designed in close(More)
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