Multilingual Video Indexing and Retrieval Employing an Information Extraction Tool for Turkish News Texts: A Case Study
In this paper, a multilingual video indexing and retrieval system is proposed which relies on an information extraction tool, a hybrid named entity recognizer, for Turkish to determine the semantic annotations for the considered videos. The system is executed on a set of news videos in English and encompasses several other components including an automatic speech recognition system for English, an English-to-Turkish machine translation system, a news video database, and a semantic video retrieval interface. The performance evaluation demonstrates that the system components achieve promising results which provides evidence for the applicability of the system. The proposed system and its application on the video set are significant as they constitute a plausible case study targeting at the problem of multilingual video indexing and retrieval utilizing information extraction as the central technique for semantic video indexing.
KeywordsMachine Translation Automatic Speech Recognition News Video Video Retrieval Automatic Speech Recognition System
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