Detail publikace
Language Recognition in iVectors Space
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.
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"
}