Structured Phonological Representations for Audio-Articulatory rtMRI Speech Classification
Real-time MRI makes it possible to observe vocal-tract articulation during speech, but mapping these articulatory patterns to phonetic and phonological categories remains challenging. We investigate whether PhonoQ, an audio-based model trained to recognize structured phonological features, provides useful information for audio--articulatory modeling. Specifically, we extract representations from PhonoQ's Conformer module, whose training is shaped by supervision for manner, place, voicing, and vowel features. Using articulatory contours with synchronized audio-derived features, we compare WavLM-large and HuBERT-large baselines with models that incorporate PhonoQ-derived representations. Ac...
| Authors | Abner Hernandez, Tomás Arias Vergara, Daiqi Liu et al. |
|---|---|
| Primary category | cs.CL |
| Published | 10 August 2026 |
| Last updated at source | 10 August 2026 |
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