Boosting retrieval of digital spoken content

  • Authors:

  • Bernardo Pereira Nunes;Alexander Mera;Marco A. Casanova;Ricardo Kawase

  • Affiliations:

  • Department of Informatics, PUC-Rio, Rio de Janeiro, RJ, Brazil,L3S Research Center, Leibniz University Hannover, Germany;Department of Informatics, PUC-Rio, Rio de Janeiro, RJ, Brazil;Department of Informatics, PUC-Rio, Rio de Janeiro, RJ, Brazil;L3S Research Center, Leibniz University Hannover, Germany

  • Venue:
  • KES'12 Proceedings of the 16th international conference on Knowledge Engineering, Machine Learning and Lattice Computing with Applications
  • Year:
  • 2012

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Abstract

Every day, the Internet expands as millions of new multimedia objects are uploaded in the form of audio, video and images. While traditional text-based content is indexed by search engines, this indexing cannot be applied to audio and video objects, resulting in a plethora of multimedia content that is inaccessible to a majority of online users. To address this issue, we introduce a technique of automatic, semantically enhanced, description generation for multimedia content. The objective is to facilitate indexing and retrieval of the objects with the help of traditional search engines. Essentially, the technique generates static Web pages automatically, which describe the content of the digital audio and video objects. These descriptions are then organized in such a way as to facilitate locating corresponding audio and video segments. The technique employs a combination of Web services and concurrently provides description translation and semantic enhancement. Thorough analysis of the click-data, comparing accesses to the digital content before and after automatic description generation, suggests a significant increase in the number of retrieval items. This outcome, however is not limited to the terms of visibility, but in supporting multilingual access, additionally decreases the number of language barriers.