Speaker segmentation and clustering

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Title: Speaker segmentation and clustering
Authors: Kotti, M
Moschou, V
Kotropoulos, C
Item Type: Journal Article
Abstract: This survey focuses on two challenging speech processing topics, namely: speaker segmentation and speaker clustering. Speaker segmentation aims at finding speaker change points in an audio stream, whereas speaker clustering aims at grouping speech segments based on speaker characteristics. Model-based, metric-based, and hybrid speaker segmentation algorithms are reviewed. Concerning speaker clustering, deterministic and probabilistic algorithms are examined. A comparative assessment of the reviewed algorithms is undertaken, the algorithm advantages and disadvantages are indicated, insight to the algorithms is offered, and deductions as well as recommendations are given. Rich transcription and movie analysis are candidate applications that benefit from combined speaker segmentation and clustering. © 2007 Elsevier B.V. All rights reserved.
Issue Date: 1-May-2008
URI: http://hdl.handle.net/10044/1/11711
DOI: http://dx.doi.org/10.1016/j.sigpro.2007.11.017
ISSN: 0165-1684
Publisher: Elsevier
Start Page: 1091
End Page: 1124
Journal / Book Title: Signal Processing
Volume: 88
Issue: 5
Copyright Statement: © 2007 Elsevier B.V. All rights reserved. NOTICE: this is the author’s version of a work that was accepted for publication in Signal Processing. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in SIGNAL PROCESSING, Vol.:88, Issue:5, (2008), DOI: 10.1016/j.sigpro.2007.11.017
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