Detail publikace

Discriminatively Trained i-vector Extractor for Speaker Verification

Originální název

Discriminatively Trained i-vector Extractor for Speaker Verification

Anglický název

Discriminatively Trained i-vector Extractor for Speaker Verification

Jazyk

en

Originální abstrakt

We have proposed a technique for discriminative training of the i-vector extractor parameters using cross-entropy as the error function. We have applied the technique both to the original i-vector extractor and to its simplified version. In both cases, the discriminative training was effective, giving higher relative improvement in the simplified case.

Anglický abstrakt

We have proposed a technique for discriminative training of the i-vector extractor parameters using cross-entropy as the error function. We have applied the technique both to the original i-vector extractor and to its simplified version. In both cases, the discriminative training was effective, giving higher relative improvement in the simplified case.

BibTex


@inproceedings{BUT76447,
  author="Ondřej {Glembek} and Lukáš {Burget} and Niko {Brümmer} and Oldřich {Plchot} and Pavel {Matějka}",
  title="Discriminatively Trained i-vector Extractor for Speaker Verification",
  annote="We have proposed a technique for discriminative training of the i-vector
extractor parameters using cross-entropy as the error function. We have applied
the technique both to the original i-vector extractor and to its simplified
version. In both cases, the discriminative training was effective, giving higher
relative improvement in the simplified case.",
  address="International Speech Communication Association",
  booktitle="Proceedings of Interspeech 2011",
  chapter="76447",
  edition="NEUVEDEN",
  howpublished="print",
  institution="International Speech Communication Association",
  number="8",
  year="2011",
  month="august",
  pages="137--140",
  publisher="International Speech Communication Association",
  type="conference paper"
}