Publication detail

Feature And Score Level Combination Of Subspace Gaussians In LVCSR Task

MOTLÍČEK, P. POVEY, D. KARAFIÁT, M.

Original Title

Feature And Score Level Combination Of Subspace Gaussians In LVCSR Task

Type

article in a collection out of WoS and Scopus

Language

English

Original Abstract

We have demonstrated that the SGMM framework is an efficient approach in the LVCSR task. Overall evaluations of SGMMs exploiting powerful but complex PLP-BN features yield similar results as those obtained by conventional HMM/GMMs. Nevertheless, the total number of SGMM parameters is about 3 times less than in the HMM/GMM framework. Evaluation results also indicate different properties of the examined acoustic modeling techniques. Although SGMMs consistently outperform HMM/GMMs when built over individual features, HMM/GMMs can benefit much more from the feature-level combination than SGMMs. Nevertheless based on an analysis measuring complementarity of individual recognition systems, we show that SGMM-based recognizers produce heterogeneous outputs (scores) and thus subsequent score-level combination can bring additional improvement.

Keywords

Automatic Speech Recognition, Discriminative features, System combination

Authors

MOTLÍČEK, P.; POVEY, D.; KARAFIÁT, M.

RIV year

2013

Released

27. 5. 2013

Publisher

IEEE Signal Processing Society

Location

Vancouver

ISBN

978-1-4799-0355-9

Book

Proceedings of ICASSP 2013

Pages from

7604

Pages to

7608

Pages count

5

URL

http://www.fit.vutbr.cz/research/groups/speech/publi/2013/motlicek_icassp2013_0007604.pdf

BibTex

@inproceedings{BUT103519,
  author="Petr {Motlíček} and Daniel {Povey} and Martin {Karafiát}",
  title="Feature And Score Level Combination Of Subspace Gaussians In LVCSR Task",
  booktitle="Proceedings of ICASSP 2013",
  year="2013",
  pages="7604--7608",
  publisher="IEEE Signal Processing Society",
  address="Vancouver",
  isbn="978-1-4799-0355-9",
  url="http://www.fit.vutbr.cz/research/groups/speech/publi/2013/motlicek_icassp2013_0007604.pdf"
}