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Novel Speech Signal Processing Algorithms for High-Accuracy Classification of Parkinson's Disease
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Formant Centralization Ratio: A Proposal for a New Acoustic Measure of Dysarthric Speech
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Incidence of Parkinson's Disease: Variation by Age, Gender, and Race/Ethnicity
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Praat: Doing Phonetics by Computer
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Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity
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The empirical mode decomposition and the Hilbert spectrum for nonlinear and non-stationary time series analysis
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Dimensionality Reduction of a Pathological Voice Quality Assessment System Based on Gaussian Mixture Models and Short-Term Cepstral Parameters
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Suitability of Dysphonia Measurements for Telemonitoring of Parkinson's Disease
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Accurate Telemonitoring of Parkinson's Disease Progression by Noninvasive Speech Tests
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Local-Learning-Based Feature Selection for High-Dimensional Data Analysis
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Speech Impairment in a Large Sample of Patients with Parkinson’s Disease
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Robust Parsimonious Selection of Dysphonia Measures for Telemonitoring of Parkinson's Disease Symptom Severity
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Classification of Parkinson's disease by using voice measurements
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Nonlinear Models Using Dirichlet Process Mixtures
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Nonlinear Models Using Dirichlet Process Mixtures
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Prediction of Parkinson’s disease based on artificial neural networks using speech datasets
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A generic optimization and learning framework for Parkinson disease via speech and handwritten records
inferred← citeshttps://doi.org/10.1007/s13198-023-01999-wopenalex-snapshot
Database processing in Chinese classics translation system based on information search and IOT speech recognition
inferred← citeshttps://doi.org/10.1007/s13369-016-2206-3openalex-snapshot
A Machine Learning System for the Diagnosis of Parkinson’s Disease from Speech Signals and Its Application to Multiple Speech Signal Types
inferred← citeshttps://doi.org/10.1007/s13369-020-04357-1openalex-snapshot
Simple Logistic Hybrid System Based on Greedy Stepwise Algorithm for Feature Analysis to Diagnose Parkinson’s Disease According to Gender
inferred← citeshttps://doi.org/10.1007/s13369-020-05080-7openalex-snapshot
Probabilistic Neural Network-based Model for Identification of Parkinson’s Disease by using Voice Profile and Personal Data
inferred← citeshttps://doi.org/10.1007/s13534-023-00283-xopenalex-snapshot
Time-frequency analysis of speech signal using Chirplet transform for automatic diagnosis of Parkinson’s disease
inferred← citeshttps://doi.org/10.1007/s13755-020-00104-wopenalex-snapshot
Bio-inspired dimensionality reduction for Parkinson’s disease (PD) classification
inferred← citeshttps://doi.org/10.1007/s40031-022-00851-2openalex-snapshot
Speech-Based Parkinson’s Disease Prediction Using XGBoost-Based Features Selection and the Stacked Ensemble of Classifiers
inferred← citeshttps://doi.org/10.1007/s42600-023-00283-xopenalex-snapshot
Bio-inspired voting ensemble weighted extreme learning machine classifier for the detection of Parkinson’s disease
inferred← citeshttps://doi.org/10.1007/s42979-020-00422-6openalex-snapshot
Robust Detection of COVID-19 in Cough Sounds
inferred← citeshttps://doi.org/10.1007/s42979-020-0099-4openalex-snapshot
Machine Learning Techniques to Identify Dementia
inferred← citeshttps://doi.org/10.1007/s42979-022-01123-yopenalex-snapshot
Data-Driven Subtyping of Parkinson’s Using Acoustic Analysis of Sustained Vowels and Cluster Analysis: Findings in the Parkinson’s Voice Initiative Study
inferred← citeshttps://doi.org/10.1007/s42979-025-04201-zopenalex-snapshot
Harnessing AI for Health and Knowledge: An Investigation into Machine and Deep Learning Models for Medical and Textual Data
inferred← citeshttps://doi.org/10.1007/s44196-025-01109-7openalex-snapshot
Classification of the Severity of Speech Disorders in Patients with Parkinson’s Disease Using Machine Learning Techniques
inferred← citeshttps://doi.org/10.1007/s44411-026-00781-1openalex-snapshot
Optimizing Voice-Based Feature Engineering and Machine Learning Pipelines for Early Parkinson’s Disease Detection
inferred← citeshttps://doi.org/10.1016/b978-0-12-396501-1.00034-0openalex-snapshot
Speech Production Modeling and Analysis
inferred← citeshttps://doi.org/10.1016/b978-0-12-818130-0.00009-xopenalex-snapshot
Intelligent Speech Processing in the Time-Frequency Domain
inferred← citeshttps://doi.org/10.1016/b978-0-12-819295-5.00008-1openalex-snapshot
Early detection of Parkinson's disease using data mining techniques from multimodal clinical data
inferred← citeshttps://doi.org/10.1016/b978-0-12-819295-5.00011-1openalex-snapshot
Conclusion and future research directions
inferred← citeshttps://doi.org/10.1016/b978-0-12-820480-1.00015-2openalex-snapshot
Promoting brain health in a digital world
inferred← citeshttps://doi.org/10.1016/b978-0-12-822548-6.00094-7openalex-snapshot
Noninvasive Multimodal Physiological Sensing Systems
inferred← citeshttps://doi.org/10.1016/b978-0-323-90037-9.00005-9openalex-snapshot
Applications of artificial intelligence to neurological disorders: current technologies and open problems
inferred← citeshttps://doi.org/10.1016/b978-0-44-330291-6.00012-3openalex-snapshot
Deep learning in Parkinson's disease
inferred← citeshttps://doi.org/10.1016/b978-0-44-331426-1.00012-7openalex-snapshot
Automated detection of Parkinson's disease using speech signals
inferred← citeshttps://doi.org/10.1016/b978-0-443-19413-9.00004-7openalex-snapshot
Deep learning for clinical decision-making and improved healthcare outcome
inferred← citeshttps://doi.org/10.1016/b978-0-443-27722-1.00001-8openalex-snapshot
Artificial intelligence in Parkinson's disease diagnosis: Multimodal biomarkers and clinical translation
inferred← citeshttps://doi.org/10.1016/b978-0-443-41459-6.00010-9openalex-snapshot
Deep learning applications in Parkinson’s disease and movement disorders
inferred← citeshttps://doi.org/10.1016/j.apacoust.2020.107528openalex-snapshot
The detection of Parkinson disease using the genetic algorithm and SVM classifier
inferred← citeshttps://doi.org/10.1016/j.apacoust.2023.109476openalex-snapshot
Proposing a new approach based on convolutional neural networks and random forest for the diagnosis of Parkinson's disease from speech signals
inferred← citeshttps://doi.org/10.1016/j.artmed.2021.102162openalex-snapshot
Replication-based regularization approaches to diagnose Reinke's edema by using voice recordings
inferred← citeshttps://doi.org/10.1016/j.asoc.2018.10.022openalex-snapshot
A comparative analysis of speech signal processing algorithms for Parkinson’s disease classification and the use of the tunable Q-factor wavelet transform
inferred← citeshttps://doi.org/10.1016/j.asoc.2025.113787openalex-snapshot
Deep insights into cognitive decline: A survey of leveraging non-intrusive modalities with deep learning techniques
inferred← citeshttps://doi.org/10.1016/j.bbe.2013.06.001openalex-snapshot
Cepstral separation difference: A novel approach for speech impairment quantification in Parkinson's disease
inferred← citeshttps://doi.org/10.1016/j.bbe.2019.05.005openalex-snapshot
Parkinson disease prediction using intrinsic mode function based features from speech signal
inferred← citeshttps://doi.org/10.1016/j.bbe.2020.01.003openalex-snapshot
Automatic Parkinson disease detection at early stages as a pre-diagnosis tool by using classifiers and a small set of vocal features
inferred← citeshttps://doi.org/10.1016/j.bbe.2020.12.009openalex-snapshot
Parkinson disease detection using energy direction features based on EMD from voice signal
inferred← citeshttps://doi.org/10.1016/j.bbe.2021.04.014openalex-snapshot
An improved framework for Parkinson’s disease prediction using Variational Mode Decomposition-Hilbert spectrum of speech signal
inferred← citeshttps://doi.org/10.1016/j.bbe.2022.04.002openalex-snapshot
End-to-end deep learning approach for Parkinson’s disease detection from speech signals
inferred← citeshttps://doi.org/10.1016/j.bbe.2022.04.003openalex-snapshot
An investigation about the relationship between dysarthria level of speech and the neurological state of Parkinson’s patients
inferred← citeshttps://doi.org/10.1016/j.bspc.2014.07.006openalex-snapshot
Automatic identification of dysprosody in idiopathic Parkinson's disease
inferred← citeshttps://doi.org/10.1016/j.bspc.2016.09.004openalex-snapshot
On the harmonic-to-noise ratio as an acoustic cue of vocal timbre of Parkinson speakers
inferred← citeshttps://doi.org/10.1016/j.bspc.2018.07.019openalex-snapshot
Thomson Multitaper MFCC and PLP voice features for early detection of Parkinson disease
inferred← citeshttps://doi.org/10.1016/j.bspc.2018.08.029openalex-snapshot
Detection of Parkinson’s disease based on voice patterns ranking and optimized support vector machine
inferred← citeshttps://doi.org/10.1016/j.bspc.2018.12.024openalex-snapshot
On the design of automatic voice condition analysis systems. Part I: Review of concepts and an insight to the state of the art
inferred← citeshttps://doi.org/10.1016/j.bspc.2019.101831openalex-snapshot
Validation of freely-available pitch detection algorithms across various noise levels in assessing speech captured by smartphone in Parkinson’s disease
inferred← citeshttps://doi.org/10.1016/j.bspc.2020.102050openalex-snapshot
Hilbert spectrum analysis for automatic detection and evaluation of Parkinson’s speech
inferred← citeshttps://doi.org/10.1016/j.bspc.2020.102165openalex-snapshot
Local discriminant preservation projection embedded ensemble learning based dimensionality reduction of speech data of Parkinson’s disease
inferred← citeshttps://doi.org/10.1016/j.bspc.2020.102350openalex-snapshot
Classification of ALS patients based on acoustic analysis of sustained vowel phonations
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102415openalex-snapshot
Analysis of voice as an assisting tool for detection of Parkinson's disease and its subsequent clinical interpretation
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102418openalex-snapshot
Advances in Parkinson's Disease detection and assessment using voice and speech: A review of the articulatory and phonatory aspects
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102452openalex-snapshot
An efficient dimensionality reduction method using filter-based feature selection and variational autoencoders on Parkinson's disease classification
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102604openalex-snapshot
A novel pre-processing technique in pathologic voice detection: Application to Parkinson’s disease phonation
inferred← citeshttps://doi.org/10.1016/j.bspc.2021.102849openalex-snapshot
Deep dual-side learning ensemble model for Parkinson speech recognition
inferred← citeshttps://doi.org/10.1016/j.bspc.2022.103688openalex-snapshot
Diagnose Parkinson’s disease and cleft lip and palate using deep convolutional neural networks evolved by IP-based chimp optimization algorithm
inferred← citeshttps://doi.org/10.1016/j.bspc.2022.104013openalex-snapshot
Automatic Parkinson’s disease detection based on the combination of long-term acoustic features and Mel frequency cepstral coefficients (MFCC)
inferred← citeshttps://doi.org/10.1016/j.bspc.2023.105087openalex-snapshot
A novel feature extraction method based on TQWT and instantaneous energy variation for Parkinson’s disease detection
inferred← citeshttps://doi.org/10.1016/j.bspc.2023.105457openalex-snapshot
Toward assessment of human voice biomarkers of brain lesions through explainable deep learning
inferred← citeshttps://doi.org/10.1016/j.bspc.2025.109302openalex-snapshot
Body sound denoising technologies: A survey and validation
inferred← citeshttps://doi.org/10.1016/j.bspc.2026.109707openalex-snapshot
Multiobjective evolutionary voice feature selection for Parkinson’s disease tele-screening
inferred← citeshttps://doi.org/10.1016/j.bspc.2026.111014openalex-snapshot
Interpretable voice-based parkinson’s detection: sex-specific acoustic biomarkers with subject-level nested cross-validation
inferred← citeshttps://doi.org/10.1016/j.cmpb.2013.05.029openalex-snapshot
Computer-aided diagnosis system: A Bayesian hybrid classification method
inferred← citeshttps://doi.org/10.1016/j.cmpb.2014.01.004openalex-snapshot
A new hybrid intelligent system for accurate detection of Parkinson's disease
inferred← citeshttps://doi.org/10.1016/j.cmpb.2014.08.007openalex-snapshot
Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease
inferred← citeshttps://doi.org/10.1016/j.cmpb.2016.08.005openalex-snapshot
A new computer vision-based approach to aid the diagnosis of Parkinson's disease
inferred← citeshttps://doi.org/10.1016/j.cmpb.2017.02.019openalex-snapshot
A two-stage variable selection and classification approach for Parkinson’s disease detection by using voice recording replications
inferred← citeshttps://doi.org/10.1016/j.cmpb.2017.11.010openalex-snapshot
A Diadochokinesis-based expert system considering articulatory features of plosive consonants for early detection of Parkinson’s disease
inferred← citeshttps://doi.org/10.1016/j.cmpb.2022.107133openalex-snapshot
Computerized analysis of speech and voice for Parkinson's disease: A systematic review
inferred← citeshttps://doi.org/10.1016/j.compbiomed.2024.109566openalex-snapshot
Multi-label speech feature selection for Parkinson’s Disease subtype recognition using graph model
inferred← citeshttps://doi.org/10.1016/j.compmedimag.2018.04.002openalex-snapshot
Exploring diagnosis and imaging biomarkers of Parkinson’s disease via iterative canonical correlation analysis based feature selection
inferred← citeshttps://doi.org/10.1016/j.csl.2014.03.003openalex-snapshot
Glottal source processing: From analysis to applications
inferred← citeshttps://doi.org/10.1016/j.csl.2021.101216openalex-snapshot
Non-negative matrix factorization-based time-frequency feature extraction of voice signal for Parkinson's disease prediction
inferred← citeshttps://doi.org/10.1016/j.csl.2021.101321openalex-snapshot
The phonetic footprint of Parkinson’s disease
inferred← citeshttps://doi.org/10.1016/j.csl.2022.101355openalex-snapshot
Intelligibility assessment of impaired speech using Regularized self-representation based compact supervectors
inferred← citeshttps://doi.org/10.1016/j.csl.2022.101411openalex-snapshot
Speech intelligibility assessment of dysarthria using Fisher vector encoding
inferred← citeshttps://doi.org/10.1016/j.csl.2026.102010openalex-snapshot
Multilingual voice signal analysis for Parkinson’s disease detection using instance-based domain adaptation through kernel mean matching
inferred← citeshttps://doi.org/10.1016/j.dadm.2014.11.012openalex-snapshot
Automatic speech analysis for the assessment of patients with predementia and Alzheimer's disease
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