Classifying Rhoticity of/ɹ/in Speech Sound Disorder using Age-and-Sex Normalized Formants

Nina R. Benway, Jonathan L. Preston, Asif Salekin, Yi Xiao, Harshit Sharma, Tara McAllister

Research output: Contribution to journalConference Articlepeer-review

3 Scopus citations

Abstract

Mispronunciation detection tools could increase treatment access for speech sound disorders impacting, e.g.,/ɹ/. We show age-and-sex normalized formant estimation outperforms cepstral representation for detection of fully rhotic vs. derhotic/ɹ/in the PERCEPT-R Corpus. Gated recurrent neural networks trained on this feature set achieve a mean test participant-specific F1-score = .81 (σx = .10, med = .83, n = 48), with post hoc modeling showing no significant effect of child age or sex.

Original languageEnglish (US)
Pages (from-to)4563-4567
Number of pages5
JournalProceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Volume2023-August
DOIs
StatePublished - 2023
Event24th International Speech Communication Association, Interspeech 2023 - Dublin, Ireland
Duration: Aug 20 2023Aug 24 2023

Keywords

  • clinical
  • mispronunciation detection
  • rhotics

ASJC Scopus subject areas

  • Language and Linguistics
  • Human-Computer Interaction
  • Signal Processing
  • Software
  • Modeling and Simulation

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