4arXiv cs.CL (Computation and Language)·
Self-supervised WavLM + DTW framework for L2 pronunciation, rhythm, and intonation scoring
Researchers propose a text-free framework for second-language (L2) speech assessment using Dynamic Time Warping (DTW) over self-supervised WavLM representations, covering phonetic accuracy, rhythm, and intonation in English and Japanese. The DTW-based approach comparing learner speech to native templates exceeds human agreement on holistic phonetic scoring, and a novel warping-path method approaches human-level rhythm assessment. Intonation scoring, combining DTW over prosodic residuals with pitch and intensity features, shows more modest results. The method requires no labeled L2 data, making it applicable in low-resource settings.
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