Abstract

This study investigates how first language (L1) phonological systems affect the stability of articulatory-to-acoustic inversion (AAI) in second language (L2) English speech using a speech foundation model-based approach. We leverage an AAI system built on WavLM-large, pretrained on 94 000 h of English audio from diverse domains and further trained to predict articulatory trajectories using electromagnetic articulography data from a native English speaker. This supervision enables the model to approximate vocal tract movements but encodes English L1 articulatory priors, limiting generalization to diverse L2 backgrounds. We hypothesize that speakers of languages with rhythmic structures and segmental inventories similar to English will exhibit more stable AAI, while speakers of more divergent L1s will show greater trajectory mismatch. Inversion performance was evaluated using a round-trip resynthesis …

Date

2025

Authors

Yoonjeong Lee, Jihwan Lee, Shrikanth Narayanan

Journal

The Journal of the Acoustical Society of America

Volume

158

Issue

4_Supplement

Pages

A194-A195

Publisher

Acoustical Society of America