Detail publikace

Employment of Subspace Gaussian Mixture Models in Speaker Recognition

MOTLÍČEK, P. DEY, S. MADIKERI, S. BURGET, L.

Originální název

Employment of Subspace Gaussian Mixture Models in Speaker Recognition

Typ

článek ve sborníku ve WoS nebo Scopus

Jazyk

angličtina

Originální abstrakt

This paper presents Subspace Gaussian Mixture Model (SGMM) approach employed as a probabilistic generative model to estimate speaker vector representations to be subsequently used in the speaker verification task. SGMMs have already been shown to significantly outperform traditional HMM/GMMs in Automatic Speech Recognition (ASR) applications. An extension to the basic SGMM framework allows to robustly estimate low-dimensional speaker vectors and exploit them for speaker adaptation. We propose a speaker verification framework based on low-dimensional speaker vectors estimated using SGMMs, trained in ASR manner using manual transcriptions. To test the robustness of the system, we evaluate the proposed approach with respect to the state-of-the-art i-vector extractor on the NIST SRE 2010 evaluation set and on four different length-utterance conditions: 3sec-10sec, 10 sec-30 sec, 30 sec-60 sec and full (untruncated) utterances. Experimental results reveal that while i-vector system performs better on truncated 3sec to 10sec and 10 sec to 30 sec utterances, noticeable improvements are observed with SGMMs especially on full length-utterance durations. Eventually, the proposed SGMM approach exhibits complementary properties and can thus be efficiently fused with i-vector based speaker verification system.

Klíčová slova

speaker recognition, i-vectors, subspace Gaussian mixture models, automatic speech recognition

Autoři

MOTLÍČEK, P.; DEY, S.; MADIKERI, S.; BURGET, L.

Rok RIV

2015

Vydáno

19. 4. 2015

Nakladatel

IEEE Signal Processing Society

Místo

South Brisbane, Queensland

ISBN

978-1-4673-6997-8

Kniha

Proceedings of 2015 IEEE International Conference on Acoustics, Speech and Signal Processing

Strany od

4445

Strany do

4449

Strany počet

5

URL

https://ieeexplore.ieee.org/document/7178811

BibTex

@inproceedings{BUT119895,
  author="Petr {Motlíček} and Subhadeep {Dey} and Srikanth {Madikeri} and Lukáš {Burget}",
  title="Employment of Subspace Gaussian Mixture Models in Speaker Recognition",
  booktitle="Proceedings of 2015 IEEE International Conference on Acoustics, Speech and Signal Processing",
  year="2015",
  pages="4445--4449",
  publisher="IEEE Signal Processing Society",
  address="South Brisbane, Queensland",
  doi="10.1109/ICASSP.2015.7178811",
  isbn="978-1-4673-6997-8",
  url="https://ieeexplore.ieee.org/document/7178811"
}

Dokumenty

motlicek_icassp2015_0004445.pdf