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Speaker segmentation and clustering

Authors
Journal
Signal Processing
0165-1684
Publisher
Elsevier
Publication Date
Volume
88
Issue
5
Identifiers
DOI: 10.1016/j.sigpro.2007.11.017
Keywords
  • Speaker Segmentation
  • Speaker Clustering
  • Diarization
Disciplines
  • Computer Science

Abstract

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.

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