• Corpus ID: 228012439

Fuzzy Restricted Boltzmann Machine based Probabilistic Linear Discriminant Analysis for Noise-Robust Text-Dependent Speaker Verification on Short Utterances

@inproceedings{Yoon2020FuzzyRB,
  title={Fuzzy Restricted Boltzmann Machine based Probabilistic Linear Discriminant Analysis for Noise-Robust Text-Dependent Speaker Verification on Short Utterances},
  author={Sung-Hyun Yoon and Min-Sung Koh and Ha-jin Yu},
  year={2020}
}
In the i-vector-based speaker verification system, it is important to compensate for session variability on the ivector to improve speaker verification performance. Linear discriminant analysis (LDA) is widely used to compensate for session variability by reducing the dimensionality of the i-vector. Restricted Boltzmann machine (RBM)-based probabilistic linear discriminant analysis (PLDA) has been proposed to improve the session variability compensation ability of LDA. It can be viewed as a… 
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