Using output probability distribution for oov word rejection

Shilei Huang*, Xiang Xie, Pascale Fung

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

This paper proposes a method to calculate the confidence score for out-of-vocabulary (OOV) word verification based on the Output Probability Distribution (OPD) of phoneme HMMs. Compared with input vector for dynamic garbage model, OPD vector contains more information than the sorted probabilities. Confidence score of each phoneme is calculated by SVM with OPD vectors as input. Hypotheses are accepted or rejected based on this confidence score. Experimental results showed that the proposed method achieved lower EER in word verification task than the conventional dynamic garbage model.

Original languageEnglish
Title of host publication2008 IEEE Workshop on Spoken Language Technology, SLT 2008 - Proceedings
Pages221-224
Number of pages4
DOIs
Publication statusPublished - 2008
Event2008 IEEE Workshop on Spoken Language Technology, SLT 2008 - Goa, India
Duration: 15 Dec 200819 Dec 2008

Publication series

Name2008 IEEE Workshop on Spoken Language Technology, SLT 2008 - Proceedings

Conference

Conference2008 IEEE Workshop on Spoken Language Technology, SLT 2008
Country/TerritoryIndia
CityGoa
Period15/12/0819/12/08

Keywords

  • Confidence measure
  • Speech recognition
  • Word verification

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