Detection of acoustic change-points in audio streams and signal segmentation
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Date
2005
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Czech Technical University
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Technická Univerzita v Liberci
Technical university of Liberec, Czech Republic
Abstract
This contribution proposes an efficient method for the detection of relevant changes in continuous stream of sound. The detected change-points can then serve for the segmentation of long audio recordings into shorter and more or less homogenous sections. First, we discuss the task of a single change-point detection using the Bayes decision theory. We show that it leads to a quite simple and computationally efficient solution based on the Bayesian Information Criterion. Next, we extend this approach to formulate the algorithm for the detection of multiple change-points. Finally, the proposed algorithm is applied for the segmentation of broadcast news audio-streams into parts belonging to different speakers or different acoustic conditions. Such segmentation is necessary as the first step in the automatic speech-to-text transcription of TV or radio news.
Description
Subject(s)
Bayesian information criterion, detection of acoustic changes, ream processing, speaker segmentation, speech processing and recognition
Citation
ISSN
1210-2512