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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. 

Abstract The relationships among the four major embryophyte lineages (mosses, liverworts, hornworts, vascular plants) and the timing of the origin of land plants are enigmatic problems in plant evolution. Here, we resolve the monophyly of bryophytes by improving taxon sampling of hornworts and eliminating the effect of synonymous substitutions. We then estimate the divergence time of crown embryophytes based on three fossil calibration strategies, and reveal that maximum calibration constraints have a major effect on estimating the time of origin of land plants. Moreover, comparison of priors and posteriors provides a guide for evaluating the optimal calibration strategy. By considering the reliability of fossil calibrations and the influences of molecular data, we estimate that land plants originated in the Precambrian (980–682 Ma), much older than widely recognized. Our study highlights the important contribution of molecular data when faced with contentious fossil evidence, and that fossil calibrations used in estimating the timescale of plant evolution require critical scrutiny.