Layer-wise aggregation from wav2vec 2.0 best predicts intelligibility in dysarthric speech, while time-wise aggregation is better for imprecise consonants, harsh voice, and monoloudness.
Speech foundation models in healthcare: Effect of layer selection on pathological speech feature prediction
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Time vs. Layer: Locating Predictive Cues for Dysarthric Speech Descriptors in wav2vec 2.0
Layer-wise aggregation from wav2vec 2.0 best predicts intelligibility in dysarthric speech, while time-wise aggregation is better for imprecise consonants, harsh voice, and monoloudness.