Title assignment for automatic topic segments in TV broadcast news
This paper addresses the task of assigning a title to topic segments automatically extracted from TV Broadcast News video recordings. We propose to associate a topic segment with the title of a newspaper article collected on the web at the same date. The task implies pairing newspaper articles and topic segments by maximising a given similarity measure. This approach raises several issues, such as the selection of candidate newspaper articles, the vectorial representation of both the segment and the articles, the choice of a suitable similarity measure, and the robustness to automatic segmentation errors. Experiments were conducted on various French TV Broadcast News shows recorded during one week, in conjunction with text articles collected through the Google News homepage at the same period. We introduce a full evaluation framework allowing the measurement of the quality of topic segment retrieval, topic title assignment and also joint retrieval and titling. The approach yields good titling performance and reveals to be robust to automatic segmentation.
2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)