Detail publikace

Language Recognition in iVectors Space

MARTÍNEZ GONZÁLEZ, D. PLCHOT, O. BURGET, L. GLEMBEK, O. MATĚJKA, P.

Originální název

Language Recognition in iVectors Space

Anglický název

Language Recognition in iVectors Space

Jazyk

en

Originální abstrakt

We have introduced a novel approach for language recognition. Three classifiers (linear generative model, SVM and logistic regression) have been tested in the iVector space, and all outperform the state-of-the-art JFA system. Very simple and fast classifier based on linear generative model provides excellent performance over all conditions. The advantage of this classifier is also its scalability: addition of a new language only requires estimating the mean over the corresponding iVectors. Most of the computational load is in the iVector generation. Hence, as a next step, we will try to obtain iVectors from the utterances and the corresponding sufficient statistics in a more direct way.

Anglický abstrakt

We have introduced a novel approach for language recognition. Three classifiers (linear generative model, SVM and logistic regression) have been tested in the iVector space, and all outperform the state-of-the-art JFA system. Very simple and fast classifier based on linear generative model provides excellent performance over all conditions. The advantage of this classifier is also its scalability: addition of a new language only requires estimating the mean over the corresponding iVectors. Most of the computational load is in the iVector generation. Hence, as a next step, we will try to obtain iVectors from the utterances and the corresponding sufficient statistics in a more direct way.

Dokumenty

BibTex


@inproceedings{BUT76437,
  author="David {Martínez González} and Oldřich {Plchot} and Lukáš {Burget} and Ondřej {Glembek} and Pavel {Matějka}",
  title="Language Recognition in iVectors Space",
  annote="We have introduced a novel approach for language recognition. Three classifiers
(linear generative model, SVM and logistic regression) have been tested in the
iVector space, and all outperform the state-of-the-art JFA system. Very simple
and fast classifier based on linear generative model provides excellent
performance over all conditions. The advantage of this classifier is also its
scalability: addition of a new language only requires estimating the mean over
the corresponding iVectors. Most of the computational load is in the iVector
generation. Hence, as a next step, we will try to obtain iVectors from the
utterances and the corresponding sufficient statistics in a more direct way.",
  address="International Speech Communication Association",
  booktitle="Proceedings of Interspeech 2011",
  chapter="76437",
  edition="NEUVEDEN",
  howpublished="print",
  institution="International Speech Communication Association",
  number="8",
  year="2011",
  month="august",
  pages="861--864",
  publisher="International Speech Communication Association",
  type="conference paper"
}