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Latest

• On Modeling Glottal Source Information for Phonation Assessment in Parkinson’s Disease
• Parallel Representation Learning for the Classification of Pathological Speech: Studies on Parkinson’s Disease and Cleft Lip and Palate
• Automatic detection of Voice Onset Time in voiceless plosives using gated recurrent units
• Multi-channel spectrograms for speech processing applications using deep learning methods
• Comparison of User Models Based on GMM-UBM and I-Vectors for Speech, Handwriting, and Gait Assessment of Parkinson’s Disease Patients
• Apkinson: the smartphone application for telemonitoring Parkinson’s patients through speech, gait and hands movement
• Articulation and Empirical Mode Decomposition Features in Diadochokinetic Exercises for the Speech Assessment of Parkinson's Disease Patients
• Convolutional Neural Networks and a Transfer Learning Strategy to Classify Parkinson’s Disease from Speech in Three Different Languages
• Apkinson
• Phonet: A Tool Based on Gated Recurrent Neural Networks to Extract Phonological Posteriors from Speech
• Surgical mask detection with deep recurrent phonetic models
• Apkinson: A Mobile Solution for Multimodal Assessment of Patients with Parkinson's Disease
• NeuroSpeech: An open-source software for Parkinson's speech analysis
• Multi-view representation learning via GCCA for multimodal analysis of Parkinson's disease
• On the impact of non-modal phonation on phonological features