Exploratory experiments combining four voice databases to evaluate XGBoost, DenseNet, and Isolation Forest on raw waveforms, spectrograms, MFCCs, and acoustic features for pathology detection, with peak F1 of 0.733.
Journal of Ma- chine Learning Research 12, 2825–2830 (2011)
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Towards Robust Voice Pathology Detection
Exploratory experiments combining four voice databases to evaluate XGBoost, DenseNet, and Isolation Forest on raw waveforms, spectrograms, MFCCs, and acoustic features for pathology detection, with peak F1 of 0.733.