Efficient approximated i-vector extraction

@article{Aronowitz2012EfficientAI,
  title={Efficient approximated i-vector extraction},
  author={Hagai Aronowitz and Oren Barkan},
  journal={2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  year={2012},
  pages={4789-4792}
}
I-vectors are currently widely used by state-of-the-art speech processing systems for tasks such as speaker verification and language identification. A shortcoming of i-vector-based systems is that the i-vector extraction process is computationally expensive. In this paper we propose an efficient method to extract i-vectors approximately. The method normalizes the GMM counts to be similar across sessions. We validate our method empirically for the speaker verification task on five different… CONTINUE READING
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Speaker verification using simplified and supervised i-vector modeling

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