Acoustic to Articulatory Speech Inversion for Children with Velopharyngeal Insufficiency

Traditional clinical approaches for assessing nasality, such as nasopharyngoscopy and nasometry, involve unpleasant experiences and are problematic for children. Speech Inversion (SI), a noninvasive technique, offers a promising alternative for estimating articulatory movement without the need for physical instrumentation. In this study, an SI system trained on nasalance data from healthy adults is augmented with source information from electroglottography and acoustically derived F0, periodic and aperiodic energy estimates as proxies for glottal control. This model achieves 16.92% relative improvement in Pearson Product-Moment Correlation (PPMC) compared to a previous SI system for nasalance estimation. To adapt the SI system for nasalance estimation in children with Velopharyngeal Insufficiency (VPI), the model initially trained on adult speech was fine-tuned using children with VPI data, yielding an 7.90% relative improvement in PPMC compared to its performance before fine-tuning.

Enhancing Acoustic-to-Articulatory Speech Inversion by Incorporating Nasality

Speech is produced through the coordination of vocal tract constricting organs: lips, tongue, velum, and glottis. Previous works developed Speech Inversion (SI) systems to recover acoustic-to-articulatory mappings for lip and tongue constrictions, called oral tract variables (TVs), which were later enhanced by including source information (periodic and aperiodic energies, and F0 frequency) as proxies for glottal control. Comparison of the nasometric measures with high-speed nasopharyngoscopy showed that nasalance can serve as ground truth, and that an SI system trained with it reliably recovers velum movement patterns for American English speakers. Here, two SI training approaches are compared: baseline models that estimate oral TVs and nasalance independently, and a synergistic model that combines oral TVs and source features with nasalance. The synergistic model shows relative improvements of 5% in oral TVs estimation and 9% in nasalance estimation compared to the baseline models.

Enhancing Speech Articulation Analysis using a Geometric Transformation of the X-ray Microbeam Dataset

Accurate analysis of speech articulation is crucial for speech analysis. However, X-Y coordinates of articulators strongly depend on the anatomy of the speakers and the variability of pellet placements, and existing methods for mapping anatomical landmarks in the X-ray Microbeam Dataset (XRMB) fail to capture the entire anatomy of the vocal tract. In this paper, we propose a new geometric transformation that improves the accuracy of these measurements. Our transformation maps anatomical landmarks' X-Y coordinates along the midsagittal plane onto six relative measures: Lip Aperture (LA), Lip Protusion (LP), Tongue Body Constriction Location (TTCL), Degree (TBCD), Tongue Tip Constriction Location (TTCL) and Degree (TTCD). Our novel contribution is the extension of the palate trace towards the inferred anterior pharyngeal line, which improves measurements of tongue body constriction.