  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 ({\sigma}x=.10, med = .83, n = 48), with post hoc modeling showing no
significant effect of child age or sex.
