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  • Direct articulatory observation reveals phoneme recognition performance characteristics of a self-supervised speech model

This content will become publicly available on November 1, 2025

Title: Direct articulatory observation reveals phoneme recognition performance characteristics of a self-supervised speech model
Variability in speech pronunciation is widely observed across different linguistic backgrounds, which impacts modern automatic speech recognition performance. Here, we evaluate the performance of a self-supervised speech model in phoneme recognition using direct articulatory evidence. Findings indicate significant differences in phoneme recognition, especially in front vowels, between American English and Indian English speakers. To gain a deeper understanding of these differences, we conduct real-time MRI-based articulatory analysis, revealing distinct velar region patterns during the production of specific front vowels. This underscores the need to deepen the scientific understanding of self-supervised speech model variances to advance robust and inclusive speech technology.  more » « less
Award ID(s):
2311676
PAR ID:
10574485
Author(s) / Creator(s):
; ; ; ; ; ; ; ;
Publisher / Repository:
AIP
Date Published:
Journal Name:
JASA Express Letters
Volume:
4
Issue:
11
ISSN:
2691-1191
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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