Analysis of i-vector Length Normalization in Speaker Recognition Systems

@inproceedings{GarciaRomero2011AnalysisOI,
  title={Analysis of i-vector Length Normalization in Speaker Recognition Systems},
  author={Daniel Garcia-Romero and Carol Y. Espy-Wilson},
  booktitle={INTERSPEECH},
  year={2011}
}
We present a method to boost the performance of probabilistic generative models that work with i-vector representations. The proposed approach deals with the nonGaussian behavior of i-vectors by performing a simple length normalization. This non-linear transformation allows the use of probabilistic models with Gaussian assumptions that yield equivalent performance to that of more complicated systems based on Heavy-Tailed assumptions. Significant performance improvements are demonstrated on the… CONTINUE READING
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Support Vector Machines versus Fast Scoring in the Low-Dimensional Total Variability Space for Speaker Verification

  • N. Dehak
  • Interspeech 2009, Brighton, UK, 2009.
  • 2009
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