# Ultrasound tongue imaging for diarization and alignment of child speech therapy sessions

arXiv: https://arxiv.org/abs/1907.00818 · HTML: https://mlsanity.com/paper/1907.00818/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Jul 2019.

## Built on by (most cited first, 3 of 3)

- [Exploiting Cross-domain And Cross-Lingual Ultrasound Tongue Imaging Features For Elderly And Dysarthric Speech Recognition](https://mlsanity.com/paper/2206.07327/) (2022)
- [Exploiting ultrasound tongue imaging for the automatic detection of speech articulation errors](https://mlsanity.com/paper/2103.00324/) (2021)
- [MoDiCoL: A Modular Diagnostic Continual Learning Dataset for Robust Speech Recognition](https://mlsanity.com/paper/2606.14459/) (2026)

## Abstract (arXiv)

We investigate the automatic processing of child speech therapy sessions using ultrasound visual biofeedback, with a specific focus on complementing acoustic features with ultrasound images of the tongue for the tasks of speaker diarization and time-alignment of target words. For speaker diarization, we propose an ultrasound-based time-domain signal which we call estimated tongue activity. For word-alignment, we augment an acoustic model with low-dimensional representations of ultrasound images of the tongue, learned by a convolutional neural network. We conduct our experiments using the Ultrasuite repository of ultrasound and speech recordings for child speech therapy sessions. For both tasks, we observe that systems augmented with ultrasound data outperform corresponding systems using only the audio signal.