Automatic Assessment of Parkinson's Disease Using Speech Representations of Phonation and Articulation
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Title
Automatic Assessment of Parkinson's Disease Using Speech Representations of Phonation and Articulation
Authors
Keywords
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Journal
IEEE-ACM Transactions on Audio Speech and Language Processing
Volume 31, Issue -, Pages 242-255
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Online
2022-11-18
DOI
10.1109/taslp.2022.3212829
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Note: Only part of the references are listed.- Advances in Parkinson's Disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects
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- (2019) Laureano Moro-Velazquez et al. Scientific Reports
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- (2018) J.C. Vásquez-Correa et al. JOURNAL OF COMMUNICATION DISORDERS
- A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform
- (2018) C. Okan Sakar et al. APPLIED SOFT COMPUTING
- Parkinson’s Disease and Aging: Analysis of Their Effect in Phonation and Articulation of Speech
- (2017) T. Arias-Vergara et al. Cognitive Computation
- The Geneva Minimalistic Acoustic Parameter Set (GeMAPS) for Voice Research and Affective Computing
- (2016) Florian Eyben et al. IEEE Transactions on Affective Computing
- Quasi Closed Phase Glottal Inverse Filtering Analysis With Weighted Linear Prediction
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- Automatic Evaluation of Articulatory Disorders in Parkinson’s Disease
- (2014) Michal Novotny et al. IEEE-ACM Transactions on Audio Speech and Language Processing
- Evaluation of speech impairment in early stages of Parkinson’s disease: a prospective study with the role of pharmacotherapy
- (2012) Jan Rusz et al. JOURNAL OF NEURAL TRANSMISSION
- Glottal inverse filtering analysis of human voice production — A review of estimation and parameterization methods of the glottal excitation and their applications
- (2011) PAAVO ALKU SADHANA-ACADEMY PROCEEDINGS IN ENGINEERING SCIENCES
- Automated Intelligibility Assessment of Pathological Speech Using Phonological Features
- (2009) Catherine Middag et al. EURASIP Journal on Advances in Signal Processing
- Formant Centralization Ratio: A Proposal for a New Acoustic Measure of Dysarthric Speech
- (2009) Shimon Sapir et al. JOURNAL OF SPEECH LANGUAGE AND HEARING RESEARCH
- Speech treatment for Parkinson’s disease
- (2008) Lorraine O Ramig et al. Expert Review of Neurotherapeutics
- Critical Analysis of the Impact of Glottal Features in the Classification of Clinical Depression in Speech
- (2007) E. Moore et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
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