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Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment
[article]
2022
arXiv
pre-print
Automatic pronunciation assessment is an important technology to help self-directed language learners. While pronunciation quality has multiple aspects including accuracy, fluency, completeness, and prosody, previous efforts typically only model one aspect (e.g., accuracy) at one granularity (e.g., at the phoneme-level). In this work, we explore modeling multi-aspect pronunciation assessment at multiple granularities. Specifically, we train a Goodness Of Pronunciation feature-based Transformer
arXiv:2205.03432v1
fatcat:jjj7grjgbjalzh62fg3fpyyare