GTTS-EHU Systems for QUESST at MediaEval 2014
This paper briefly describes the systems presented by the Software Technologies Working Group (http://gtts.ehu.es, GTTS) of the University of the Basque Country (UPV/EHU) to the Query-by-Example Search on Speech Task (QUESST) at MediaEval 2014. The GTTS-EHU systems consist of four modules: (1) feature extraction; (2) speech activity detection; (3) DTW-based query matching; and (4) score calibration and fusion. The submitted systems follow the same approach used in our SWS 2013 submissions, with two minor changes (needed to address the new task): the search stops at the most likely query detection (no further detections are looked for) and a score is produced for each (query, document) pair. The two approximate matching types introduced in QUESST have not received special treatment. This year, we have just explored the use of reduced feature sets, obtaining worse results but at lower computational costs.
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