A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2022; you can also visit the original URL.
The file type is
In addition, we conduct an open test on a separate UTD-4Accents dataset, where our system recognition outputs show a strong correlation with human perception, based on accentedness and intelligibility. ... We show that fine-tuning with pseudo labels achieves a 5.35% phoneme error rate reduction and 2.48% MDD F1 score improvement over a labeled-samples-only fine-tuning baseline. ... In this study, we focus on detecting phonetic-level pronunciation errors for L2 speech intelligibility and accentedness assessment. ...arXiv:2203.15937v3 fatcat:itrevkthgrbklk6ha27iysgpta