Automated pronunciation scoring using confidence scoring and landmark-based SVM

Su Youn Yoon, Mark Allan Hasegawa-Johnson, Richard Sproat

Research output: Contribution to journalArticle

Abstract

In this study, we present a pronunciation scoring method for second language learners of English (hereafter, L2 learners). This study presents a method using both confidence scoring and classifiers. Classifiers have an advantage over confidence scoring for specialization in the specific phonemes where L2 learners make frequent errors. Classifiers (Landmark-based Support Vector Machines) were trained in order to distinguish L2 phonemes from their frequent substitution patterns. In this study, the method was evaluated on the specific English phonemes where L2 English learners make frequent errors. The results suggest that the automated pronunciation scoring method can be improved consistently by combining the two methods.

Original languageEnglish (US)
Pages (from-to)1903-1906
Number of pages4
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
StatePublished - 2009

Keywords

  • Confidence score
  • Landmark Support Vector Machine
  • Speech recognition

ASJC Scopus subject areas

  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Sensory Systems

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