Automatic Discovery of Salient Segments in Imperfect Speech Transcripts

This paper addresses the problem of automatic detection of salient video segments for real-world applications such as corporate training based on associated speech transcriptions. We present a novel segmentation algorithm based on automatic speech recognition (ASR) applied to the audio track of the video. Our feature set consists of word n-grams extracted from the imperfect speech transcriptions. We use a two-pass algorithm that combines a boundary-based method with a content-based method. In the first pass, we analyze the temporal distribution and the rate of arrival of features to compute an initial segmentation. In the second pass, we detect changes in content-bearing words by using the content-bearing features as queries in an information retrieval system. The content-based second pass validates the initial segments and merges them as needed. Variations in the structure of the audio/video content, and the accuracy of ASR have an impact on the feasibility of the segmentation task. ...

• Type: Conference
• Year: 2001
• Where: CIKM
• Authors: Dulce B. Ponceleon, Savitha Srinivasan
• Keywords: Associated Speech Transcriptions, CIKM 2001, Information Management, Salient Video Segments, Speech Transcriptions