History-based visual mining of semi-structured audio and text

Bouamrane, Matt-Mouley; Luz, Saturnino; Masoodian, Masood

doi:10.1109/MMMC.2006.1651349

Files

History-Based Visual Mining of Semi-Structured Audio and Text.pdf

148.5Kb

Bouamrane, M. – M., Luz, S. & Masoodian, M. (2006) History based visual mining of semi-structured audio and text. In Proceedings of the 12th International Multi-media modelling conference, MMM2006, Beijing, China, Jan, 2006(pp.360-363). Washington, DC, USA: IEEE Computer Society.

Permanent Research Commons link: https://hdl.handle.net/10289/1700

Abstract

Accessing specific or salient parts of multimedia recordings remains a challenge as there is no obvious way of structuring and representing a mix of space-based and time-based media. A number of approaches have been proposed which usually involve translating the continuous component of the multimedia recording into a space-based representation, such as text from audio through automatic speech recognition and images from video (keyframes). In this paper, we present a novel technique which defines retrieval units in terms of a log of actions performed on space-based artefacts, and exploits timing properties and extended concurrency to construct a visual presentation of text and speech data. This technique can be easily adapted to any mix of space-based artefacts and continuous media.

Date

2006

Type

Conference Contribution

Publisher

IEEE Computer Society

Rights

This article has been published in Proceedings of the 12th International Multi-media modelling conference, MMM2006, Beijing, China, Jan, 2006. ©2006 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.

Collections

Computing and Mathematical Sciences Papers [1164]