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

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 /r/ 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.

To appear in Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2023