Purpose: The purpose of this article is to orient both clinicians and researchers to machine
learning (ML) approaches as applied to the field of speech-language pathology. We first …

Open science practices have led to an increase in available speech datasets for researchers
interested in acoustic analysis. Accurate evaluation of these databases frequently requires …

Purpose: This feasibility trial describes changes in rhotic production in residual speech
sound disorder following ten 40-min sessions including artificial intelligence (AI)-assisted …

Mispronunciation detection tools could increase treatment access for speech sound
disorders impacting, eg,/r/. We show age-and-sex normalized formant estimation …

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 …

Acoustic-to-articulatory speech inversion could enhance automated clinical
mispronunciation detection to provide detailed articulatory feedback unattainable by formant …

The effects of different acoustic representations and normalizations were compared for
classifiers predicting perception of children's rhotic versus derhotic/ò/. Formant and Mel …

The advancement in deep learning and internet-of-things have led to diverse human
sensing applications. However, distinct patterns in human sensing, influenced by various …

Our purpose is to highlight the contributions of TalkBank initiatives to improved
understanding of clinical impairments in adult and child speakers and examine remaining …

balaji1312@ ucla. edu; amberafshan@ ucla. edu; ajohnson49@ ucla. edu; aurosweta99@
ucla. edu; alemartin@ ucla. edu; michaelni12@ ucla. edu; haewon@ mit. edu; mquint30 …