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In the talk, I will discuss content-based retrieval in audio-visual collections. I will focus on retrieval of relevant segments of video using a textual query. In addition, I will describe techniques for detecting hyperlinks within audio-visual collections. Our retrieval system ranked first in the MediaEval 2014 Search and Hyperlinking shared task. The experiments were performed on almost 4000 hours of BBC broadcast video.
As the segmentation of the recordings shows to be crucial for high-quality video retrieval and hyperlinking, I will focus on segmentation strategies. I will show the possibility of employment of the prosodic and visual information into the segmentation process. Our decision tree-based segmentation proved to outperform fixed-length segmentation which regularly achieves the best results in the retrieval process. Visual and prosodic similarity are also explored in addition to the hyperlinking based on the subtitles and automatic transcripts. The employment of the visual similarity achieves a constant improvement, while the employment of the prosodic similarity shows a small but promising improvement too.