# Acoustic-to-Articulatory Speech Inversion Features for Mispronunciation Detection of /r/ in Child Speech Sound Disorders

arXiv: https://arxiv.org/abs/2305.16085 · HTML: https://mlsanity.com/paper/2305.16085/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 25 May 2023.

## Built on by (most cited first, 1 of 1)

- [Speaker- and Text-Independent Estimation of Articulatory Movements and Phoneme Alignments from Speech](https://mlsanity.com/paper/2407.03132/) (2024)

## Abstract (arXiv)

Acoustic-to-articulatory speech inversion could enhance automated clinical mispronunciation detection to provide detailed articulatory feedback unattainable by formant-based mispronunciation detection algorithms; however, it is unclear the extent to which a speech inversion system trained on adult speech performs in the context of (1) child and (2) clinical speech. In the absence of an articulatory dataset in children with rhotic speech sound disorders, we show that classifiers trained on tract variables from acoustic-to-articulatory speech inversion meet or exceed the performance of state-of-the-art features when predicting clinician judgment of rhoticity. Index Terms: rhotic, speech sound disorder, mispronunciation detection