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Speaker Detection in Audio Stream via Probabilistic Prediction Using Generalized GEBI

  • Koki Sakata
  • Shota Sakashita
  • Kazuya Matsuo
  • Shuichi KurogiEmail author
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9950)

Abstract

This paper presents a method of speaker detection using probabilistic prediction for avoiding the tuning of thresholds to detect a speaker in an audio stream. We introduce g-GEBI (generalized GEBI) as a generalization of BI (Bayesian Inference) and GEBI (Gibbs-distribution-based Extended BI) to execute iterative detection of a speaker in audio stream uttered by more than one speaker. Then, we show a method of probabilistic prediction in multiclass classification to classify the results of speaker detection. By means of numerical experiments using recorded real speech data, we examine the properties and the effectiveness of the present method. Especially, we show that g-GEBI and g-BI (generalized BI) are more effective than the conventional BI and GEBI in incremental speaker detection task.

Keywords

Probabilistic prediction Speaker detection Generalized Gibbs-distribution-based extended Bayesian inference 

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Copyright information

© Springer International Publishing AG 2016

Authors and Affiliations

  • Koki Sakata
    • 1
  • Shota Sakashita
    • 1
  • Kazuya Matsuo
    • 1
  • Shuichi Kurogi
    • 1
    Email author
  1. 1.Kyushu Institute of TechnologyKitakyushuJapan

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