Phonetic confusion matrix based spoken document retrieval
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Learning video browsing behavior and its application in the generation of video previews
MULTIMEDIA '01 Proceedings of the ninth ACM international conference on Multimedia
Streaming-Media Knowledge Discovery
Computer
Automated Alignment and Annotation of Audio-Visual Presentations
ECDL '02 Proceedings of the 6th European Conference on Research and Advanced Technology for Digital Libraries
Automatic generation of conference video proceedings
Journal of Visual Communication and Image Representation
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algorithm for the segmentation of an audio/video source into topically cohesive segments based on automatic speech recognition (ASR) transcriptions is presented. A novel two-pass algorithm is described that combines a boundary-based method with a content-based method. In the first pass, the temporal proximity and the rate of arrival of ngram features is analyzed in order to compute an initial segmentation. In the content- based second pass, changes in content-bearing words are detected by using the ngram features as queries in an information-retrieval system. The second pass validates the initial segments and merges them as needed. Feasibility of the segmentation task can vary enormously depending on the structure of the audio content, and the accuracy of ASR. For real-world corporate training data our method identifies, at worst, a single salient segment of the audio and, at best, a high-level table-of-contents. We illustrate the algorithm in detail with some examples and validate the results with segmentation boundaries generated manually.