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Conference Paper

Automatic annotation of media field recordings

MPS-Authors
http://pubman.mpdl.mpg.de/cone/persons/resource/persons4

Auer,  Eric
The Language Archive, MPI for Psycholinguistics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons216

Wittenburg,  Peter
The Language Archive, MPI for Psycholinguistics, Max Planck Society;

http://pubman.mpdl.mpg.de/cone/persons/resource/persons172

Sloetjes,  Han
The Language Archive, MPI for Psycholinguistics, Max Planck Society;

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Fulltext (public)

avatech-ecai2010.pdf
(Preprint), 532KB

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There is no public supplementary material available
Citation

Auer, E., Wittenburg, P., Sloetjes, H., Schreer, O., Masneri, S., Schneider, D., et al. (2010). Automatic annotation of media field recordings. In C. Sporleder, & K. Zervanou (Eds.), Proceedings of the ECAI 2010 Workshop on Language Technology for Cultural Heritage, Social Sciences, and Humanities (LaTeCH 2010) (pp. 31-34). Lisbon: University de Lisbon. Retrieved from http://ilk.uvt.nl/LaTeCH2010/.


Cite as: http://hdl.handle.net/11858/00-001M-0000-0012-CE12-B
Abstract
In the paper we describe a new attempt to come to automatic detectors processing real scene audio-video streams that can be used by researchers world-wide to speed up their annotation and analysis work. Typically these recordings are taken in field and experimental situations mostly with bad quality and only little corpora preventing to use standard stochastic pattern recognition techniques. Audio/video processing components are taken out of the expert lab and are integrated in easy-to-use interactive frameworks so that the researcher can easily start them with modified parameters and can check the usefulness of the created annotations. Finally a variety of detectors may have been used yielding a lattice of annotations. A flexible search engine allows finding combinations of patterns opening completely new analysis and theorization possibilities for the researchers who until were required to do all annotations manually and who did not have any help in pre-segmenting lengthy media recordings.