@inproceedings{marietho:2002:icslp,
  author = {J. Mari�thoz and S. Bengio},
  title  = {A Comparative Study of Adaptation Methods for Speaker Verification},
  booktitle = {Proceedings of the International Conference on Spoken Language Processing, {ICSLP}},
  year = 2002,
  url = {publications/ps/mariethoz_2002_icslp.ps.gz},
  pdf = {publications/pdf/mariethoz_2002_icslp.pdf},
  djvu = {publications/djvu/mariethoz_2002_icslp.djvu},
  original= {2002/adaptive_speaker_icslp},
  idiap = {publications/pdf/rr-01-34.pdf},
  topics = {biometric_authentication},
  abstract = {Real-life speaker verification systems are often implemented using client model adaptation methods, since the amount of data available for each client is often too low to consider plain Maximum Likelihood methods.  While the {\em Bayesian Maximum A Posteriori} (MAP) adaptation method is commonly used in speaker verification, other methods have proven to be successful in related domains such as speech recognition.  This paper proposes an experimental comparison between three well-known adaptation methods, namely MAP, {\em Maximum Likelihood Linear Regression}, and finally {\em EigenVoices}. All three methods are compared to the more classical {\em Maximum Likelihood} method, and results are given for a subset of the {\em 1999 NIST Speaker Recognition Evaluation} database.},
  categorie = {C}
}

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