Speaker Recognition in Orthogonal Complement of Time Session Variability Subspace

  • Satoru TsugeEmail author
  • Shingo Kuroiwa
Conference paper
Part of the Smart Innovation, Systems and Technologies book series (SIST, volume 98)


A time session variability between the enrollment data and the recognized data degrades speaker recognition performance. Hence, the time session variability is one of the most important issues in the speaker recognition technology. In this paper, we propose a robust speaker recognition method for the time session variability. The proposed method estimates a time session variability subspace. Then, the proposed method carries out the speaker recognition in the orthogonal complement of the time session variability subspace. In addition, we incorporate a linear discriminant analysis method into the proposed method. In order to evaluate the proposed method, we conducted a speaker identification experiment. Experimental results show that the proposed method improves speaker identification performance of baseline.


Speaker recognition i-vector Time session variability Deflation Orthogonal complement 



This work was supported by JSPS KAKENHI Grant Number JP16K00229.


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© Springer International Publishing AG, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Daido UniversityNagoyaJapan
  2. 2.Chiba UniversityChibaJapan

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