Prospective Validation of Motor-Based Intervention with Automated Mispronunciation Detection of Rhotics in Residual Speech Sound Disorders

Nina R. Benway, Jonathan L. Preston

Research output: Contribution to journalConference Articlepeer-review

3 Scopus citations

Abstract

Because lab accuracy of clinical speech technology systems may be overoptimistic, clinical validation is vital to demonstrate system reproducibility-in this case, the ability of the PERCEPT-R Classifier to predict clinician judgment of American English/ɹ/during ChainingAI motor-based speech sound disorder intervention. All five participants experienced statistically-significant improvement in untreated words following 10 sessions of combined human-ChainingAI treatment. These gains, despite a wide range of PERCEPT-human and human-human (F1-score) agreement, raise questions about best measuring classification performance for clinical speech that may be perceptually ambiguous.

Original languageEnglish (US)
Pages (from-to)4558-4562
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

  • rhotics
  • speech sound disorder

ASJC Scopus subject areas

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

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