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Depression assessment in people with Parkinson's disease: The combination of acoustic features and natural language processing.

, , , , , , and . Speech Commun., (2022)

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Transfer learning helps to improve the accuracy to classify patients with different speech disorders in different languages., , , , , , and . Pattern Recognit. Lett., (2021)Representation Learning Strategies to Model Pathological Speech: Effect of Multiple Spectral Resolutions., , , and . CoRR, (2022)One System to Rule them All: a Universal Intent Recognition System for Customer Service Chatbots., , , , and . CoRR, (2021)Comparison of User Models Based on GMM-UBM and I-Vectors for Speech, Handwriting, and Gait Assessment of Parkinson's Disease Patients., , , and . ICASSP, page 6544-6548. IEEE, (2020)Empirical Mode Decomposition articulation feature extraction on Parkinson's Diadochokinesia., , , , and . Comput. Speech Lang., (2022)Novel Speech Recognition Systems Applied to Forensics within Child Exploitation: Wav2vec2.0 vs. Whisper., and . Sensors, 23 (4): 1843 (February 2023)Characterisation of voice quality of Parkinson's disease using differential phonological posterior features., , , , , and . Comput. Speech Lang., (2017)Multimodal I-vectors to Detect and Evaluate Parkinson's Disease., , , and . INTERSPEECH, page 2349-2353. ISCA, (2018)Emotion recognition from speech under environmental noise conditions using wavelet decomposition., , , , , and . ICCST, page 247-252. IEEE, (2015)Time Dependent ARMA for Automatic Recognition of Fear-Type Emotions in Speech., , , , , and . TSD, volume 9302 of Lecture Notes in Computer Science, page 96-104. Springer, (2015)