Spoken language recognition using support vector machines with generative front-end

Kong Aik Lee, Changhuai You, Haizhou Li

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

13 Citations (Scopus)

Abstract

This paper introduces a spoken language recognition system with a generative front-end and a discriminative backend. The generative front-end is built upon an ensemble of Gaussian densities. These Gaussian densities are trained to represent elementary speech sound units characterizing a wide variety of languages. We formulate the generative front-end in a form of sequence kernel. This sequence kernel transforms a spoken utterance into a feature vector with its attributes representing the occurrence statistics of the speech sound units. A discriminative support vector machine (SVM) then operates on the feature vectors to make classification decision. The proposed language recognition system demonstrates competitive performance on NIST 1996, 2003 and 2005 LRE corpora.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages4153-4156
Number of pages4
DOIs
Publication statusPublished - Apr 2008
Externally publishedYes
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 20084 Apr 2008

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Country/TerritoryUnited States
CityLas Vegas, NV
Period31/03/084/04/08

Keywords

  • Language recognition
  • Sequence kernel
  • Support vector machine

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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