Automatic analysis of pronunciations for children with speech sound disorders

Shiran Dudy, Steven Bedrick, Meysam Asgari, Alexander Kain

Research output: Contribution to journalArticle

5 Scopus citations

Abstract

Computer-Assisted Pronunciation Training (CAPT) systems aim to help a child learn the correct pronunciations of words. However, while there are many online commercial CAPT apps, there is no consensus among Speech Language Therapists (SLPs) or non-professionals about which CAPT systems, if any, work well. The prevailing assumption is that practicing with such programs is less reliable and thus does not provide the feedback necessary to allow children to improve their performance. The most common method for assessing pronunciation performance is the Goodness of Pronunciation (GOP) technique. Our paper proposes two new GOP techniques. We have found that pronunciation models that use explicit knowledge about error pronunciation patterns can lead to more accurate classification whether a phoneme was correctly pronounced or not. We evaluate the proposed pronunciation assessment methods against a baseline state of the art GOP approach, and show that the proposed techniques lead to classification performance that is more similar to that of a human expert.

Original languageEnglish (US)
Pages (from-to)62-84
Number of pages23
JournalComputer Speech and Language
Volume50
DOIs
StatePublished - Jul 1 2018

Keywords

  • Diagnostic tools
  • Educational software
  • Goodness of Pronunciation
  • Speech disorders
  • Speech recognition
  • Support Vector Machine

ASJC Scopus subject areas

  • Software
  • Theoretical Computer Science
  • Human-Computer Interaction

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