CONTENTUS—technologies for next generation multimedia libraries: Automatic multimedia processing for semantic search
An ever-growing amount of digitized content urges libraries and archives to integrate new media types from a large number of origins such as publishers, record labels and film archives, into their existing collections. This is a challenging task, since the multimedia content itself as well as the as...
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Veröffentlicht in: | Multimedia tools and applications 2013-03, Vol.63 (2), p.287-329 |
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Zusammenfassung: | An ever-growing amount of digitized content urges libraries and archives to integrate new media types from a large number of origins such as publishers, record labels and film archives, into their existing collections. This is a challenging task, since the multimedia content itself as well as the associated metadata is inherently heterogeneous—the different sources lead to different data structures, data quality and trustworthiness. This paper presents the
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approach towards an automated media processing chain for cultural heritage organizations and content holders. Our workflow allows for unattended processing from media ingest to availability thorough our search and retrieval interface. We aim to provide a set of tools for the processing of digitized print media, audio/visual, speech and musical recordings. Media specific functionalities include quality control for digitization of still image and audio/visual media and restoration of the most common quality issues encountered with these media. Furthermore, the
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tools include modules for content analysis like segmentation of printed, audio and audio/visual media, optical character recognition (OCR), speech-to-text transcription, speaker recognition and the extraction of musical features from audio recordings, all aimed at a textual representation of information inherent within the media assets. Once the information is extracted and transcribed in textual form, media independent processing modules offer extraction and disambiguation of named entities and text classification. All
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modules are designed to be flexibly recombined within a scalable workflow environment using cloud computing techniques. In the next step analyzed media assets can be retrieved and consumed through a search interface using all available metadata. The search engine combines Semantic Web technologies for representing relations between the media and entities such as persons, locations and organizations with a full-text approach for searching within transcribed information gathered through the preceding processing steps. The
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unified search interface integrates text, images, audio and audio/visual content. Queries can be narrowed and expanded in an exploratory manner, search results can be refined by disambiguating entities and topics. Further, semantic relationships become not only apparent, but can also be navigated. |
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ISSN: | 1380-7501 1573-7721 |
DOI: | 10.1007/s11042-011-0971-2 |