Classifying Rhoticity of /ɹ/ in Speech Sound Disorder using Age-and-Sex Normalized Formants
Year: 2023
Type: conference-paper
Abstract: Mispronunciation detection tools could increase treatment access for speech sound disorders impacting, e.g., /r/. We show age-and-sex normalized formant estimation outperforms cepstral representation for detection of fully rhotic vs. derhotic /r/ 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.
Source: Interspeech (USB)
Institutions: Syracuse University, Haskins Laboratories, New York University
Language: English
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: green
Awards: G2012193450, G4265142103, Biofeedback-Enhanced Treatment for Sensorimotor Learning in Speech Sound Disorders: Clinical Trial and Delineation of Subtypes, CC*DNI Engineer: Leading the Way for Research Computing at Syracuse University and Beyond, CC-NIE Networking Infrastructure: Enhancing the OrangeGrid - Upgrading the Syracuse Campus Network to Enable High Throughput Research Computing
OpenAlex ID: W4385822842