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Speaker Diarization of Multi-party Conversations Using Participants Role Information: Political Debates and Professional Meetings

  • Fabio Valente
  • Alessandro Vinciarelli
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8045)

Abstract

Speaker Diarization aims at inferring who spoke when in an audio stream and involves two simultaneous unsupervised tasks: (1) the estimation of the number of speakers, and (2) the association of speech segments to each speaker. Most of the recent efforts in the domain have addressed the problem using machine learning techniques or statistical methods (for a review see [11]) ignoring the fact that the data consists of instances of human conversations.

Keywords

Automatic Speech Recognition Speech Segment Acoustic Vector Speaker Diarization Meeting Recording 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2014

Authors and Affiliations

  • Fabio Valente
    • 1
  • Alessandro Vinciarelli
    • 1
    • 2
  1. 1.Idiap Research InstituteMartignySwitzerland
  2. 2.University of GlasgowGlasgowUK

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