Memory and Computation Trade-Offs for Efficient I-Vector Extraction

@article{Cumani2013MemoryAC,
  title={Memory and Computation Trade-Offs for Efficient I-Vector Extraction},
  author={Sandro Cumani and Pietro Laface},
  journal={IEEE Transactions on Audio, Speech, and Language Processing},
  year={2013},
  volume={21},
  pages={934-944}
}
This work aims at reducing the memory demand of the data structures that are usually pre-computed and stored for fast computation of the i-vectors, a compact representation of spoken utterances that is used by most state-of-the-art speaker recognition systems. We propose two new approaches allowing accurate i-vector extraction but requiring less memory, showing their relations with the standard computation method introduced for eigenvoices, and with the recently proposed fast eigen… CONTINUE READING
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