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

• DOI: 10.21437/interspeech.2023-312
• Publication Date: 2023-08-14T08:22:20Z
• Authors: Nina R Benway; Jonathan L Preston; Asif Salekin; Yi Xiao; Harshit Sharma; Tara McAllister
• Keywords: Audio and Speech Processing (eess.AS); FOS: Electrical engineering, electronic engineering, information engineering; Electrical Engineering and Systems Science - Audio and Speech Processing

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.<br/>To appear in Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2023<br/>