In this paper we describe a system we have developed for automatic broadcast-quality video indexing that successfully combines results from the fields of speaker verification, acoustic analysis, very large vocabulary speech recognition, content based sampling of video, information retrieval, natural language processing, dialogue systems, and MPEG2 delivery over IP. Our audio classification and ...

BACKGROUND Multicentre drug use evaluations are described in the literature infrequently and usually publish only the results. The purpose of this paper is to describe the experience of Queensland hospitals participating in the Community-Acquired Pneumonia Towards Improving Outcomes Nationally (CAPTION) project, specifically evaluating the implementation of this project, detailing benefits and ...

ors: High-level structure and summarization Researchers have considered a variety of video summarization methods—that is, methods for condensing content into a shorter descriptive form of the original content.3 Video skim, for example, is a temporally condensed form of the video stream that should preserve the most important information. Another form of summary, video highlights, aims to includ...

Multimedia content may be supplemented with time-aligned closed captions for accessibility. Often these captions are created manually by professional editors — an expensive and timeconsuming process. In this paper, we present a novel approach to automatic creation of a well-formatted, readable transcript for a video from closed captions or ASR output. Our approach uses acoustic and lexical feat...

Most speech recognition systems try to reconstruct a word sequence given an acoustic input, using prior information about the language being spoken. In some cases, there is more information available to the decoder than simply the acoustics. When decoding a television news broadcast, for example, the closed-caption information that is often recorded for hearing impaired viewers may also be avai...

We have developed Name-It, a system that associates faces and names in news videos. The system is given news videos, which include image sequences and transcripts obtained from audio tracks or closed caption texts. The system can then either infer possible name candidates for a given face, or locate a face in news videos by name. To accomplish this task, the system takes a multi-modal video ana...

We have developed Name-It, a system that associates faces and names in news videos. The system is given news videos, which include image sequences and transcripts obtained from audio tracks or closed caption texts. The system can then either infer possible name candidates for a given face, or locate a face in news videos by name. To accomplish this task, the system takes a multi-modal video ana...

Live closed-captions for deaf and hard of hearing audiences are currently produced by stenographers, or by voice writers using speech recognition. Both techniques can produce captions with errors. We are currently developing a correction module that allows a user to intercept the real-time caption stream and correct it before it is broadcast. We report results of preliminary experiments on corr...