ASR transcriptions and word-boundary timestamps as classification features raise balanced accuracy for dysarthria severity to 83.72 percent on a Korean dataset, beating waveform and deep-model baselines.
Experimental Setup We used the same corpus to train the ASR system and au- tomatic severity classification model
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Speech Recognition-based Feature Extraction for Enhanced Automatic Severity Classification in Dysarthric Speech
ASR transcriptions and word-boundary timestamps as classification features raise balanced accuracy for dysarthria severity to 83.72 percent on a Korean dataset, beating waveform and deep-model baselines.