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Transformer-Based Multi-Aspect Multi-Granularity Non-Native English Speaker Pronunciation Assessment
Yuan Gong, Ziyi Chen, Iek-Heng Chu, Peng Chang, James Glass
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 (GOPT) with multi-task learning. Experiments show that GOPT achieves the best results on speechocean762 with a public automatic speech recognition (ASR) acoustic model trained on Librispeech.
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Phone-level pronunciation scoring | speechocean762 | GOPT-PAII | Pearson correlation coefficient (PCC) | 0.68 | #3 of 8 | Archive leaderboard | report |
| Phone-level pronunciation scoring | speechocean762 | GOPT-Librispeech | Pearson correlation coefficient (PCC) | 0.61 | #7 of 8 | Archive leaderboard | report |
| Utterance-level pronounciation scoring | speechocean762 | GOPT-Librispeech | Pearson correlation coefficient (PCC) | 0.74 | #4 of 5 | Archive leaderboard | report |
| Utterance-level pronounciation scoring | speechocean762 | GOPT-PAII | Pearson correlation coefficient (PCC) | 0.73 | #5 of 5 | Archive leaderboard | report |
| Word-level pronunciation scoring | speechocean762 | GOPT-PAII | Pearson correlation coefficient (PCC) | 0.60 | #3 of 5 | Archive leaderboard | report |
| Word-level pronunciation scoring | speechocean762 | GOPT-Librispeech | Pearson correlation coefficient (PCC) | 0.55 | #5 of 5 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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