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Improving Mispronunciation Detection with Wav2vec2-based Momentum Pseudo-Labeling for Accentedness and Intelligibility Assessment
[article]
2022
arXiv
pre-print
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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