AURORA Model of Formant-to-Tongue Inversion for Didactic and Clinical Applications

TL;DR

The paper introduces the AURORA model that predicts tongue shape from formant data, serving as an educational and biofeedback tool for phonetics and speech therapy, based on ultrasound and acoustic data from native English speakers.

Contribution

It presents a novel computational model linking formant values to tongue shape, with tools for didactic and clinical applications, grounded in ultrasound and acoustic data.

Findings

Qualitative evaluation of tongue feature predictions

Development of accessible tools like a Shiny app and biofeedback software

Potential applications in phonetics education and speech therapy

Abstract

This paper outlines the conceptual and computational foundations of the AURORA (Acoustic Understanding and Real-time Observation of Resonant Articulations) model. AURORA predicts tongue displacement and shape in vowel sounds based on the first two formant values. It is intended as a didactic aid helping to explain the relationship between formants and the underlying articulation, as well as a foundation for biofeedback applications. The model is informed by ultrasound tongue imaging and acoustic data from 40 native speakers of English. In this paper we discuss the motivation for the model, the modelling objectives as well as the model architecture. We provide a qualitative evaluation of the model, focusing on selected tongue features. We then present two tools developed to make the model more accessible to a wider audience, a Shiny app and a prototype software for real-time tongue biofeedback. Potential users include students of phonetics, linguists in fields adjacent to phonetics, as well as speech and language therapy practitioners and clients.