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Diagnostics
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Pathological Speech Classification and Processing for Advanced Medical Diagnosis
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Pathological Speech Classification and Processing for Advanced Medical Diagnosis

A Special Issue of Diagnostics (ISSN 2075-4418) belonging to the section "Machine Learning and Artificial Intelligence in Diagnostics".

Deadline for manuscript submissions: 31 December 2026 | Viewed by 4588

Editor

Prof. Dr. Juan Rafael Orozco-Arroyave

E-Mail Website
Guest Editor
1. GITA Lab, Faculty of Engineering, University of Antioquia, Medellín, Colombia
2. LME Laboratory, University of Erlangen, 91054 Erlangen, Germany
Interests: computer science; artificial intelligence; signals processing; biomedical engineering; speech processing
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The Special Issue "Pathological Speech Classification and Processing for Advanced Medical Diagnosis" delves into the emerging field of pathological speech analysis, examining its potential in enhancing medical diagnosis. This Special Issue highlights innovative techniques and methodologies for speech recognition, analysis, and processing in diseased states, aiming to improve the accuracy and efficiency of clinical assessments. By exploring the latest advancements in this domain, it aims to foster a better understanding of pathological speech patterns and their application in precision medicine.

Prof. Dr. Juan Rafael Orozco-Arroyave
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Diagnostics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • pathological speech
  • medical diagnosis
  • classification and processing
  • Parkinson's disease
  • hypokinetic dysarthria
  • dysarthria
  • aphasia
  • voice disorders
  • dysphonia
  • AI

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Published Papers (2 papers)

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Research

15 pages, 1200 KB  
Article
Longitudinal Evaluation of Dysarthria Progression in Patients with Parkinson’s Disease
by Wilmar Alesander Vásquez-Barrientos, Daniel Escobar-Grisales, Cristian David Ríos-Urrego and Juan Rafael Orozco-Arroyave
Diagnostics 2026, 16(5), 683; https://doi.org/10.3390/diagnostics16050683 - 26 Feb 2026
Viewed by 1147
Abstract
Background/Objectives: Automatic evaluation of Parkinson’s disease (PD) progression is an emerging topic that deserves special attention from the research community. Unobtrusive, low-cost technology is essential for monitoring PD patients in remote areas. This paper proposes the use of phonological posteriors to create models [...] Read more.
Background/Objectives: Automatic evaluation of Parkinson’s disease (PD) progression is an emerging topic that deserves special attention from the research community. Unobtrusive, low-cost technology is essential for monitoring PD patients in remote areas. This paper proposes the use of phonological posteriors to create models that allow the progression of dysarthria level progression to be modelled based on speech recordings. Methods: Eighteen Gated Recurrent Units (GRUs) are used to estimate an equal number of phonological classes assigned to each phoneme pronounced in a given recording. Classification models of PD vs. healthy control (HC) subjects are trained with recordings of the PC-GITA corpus. This information is used in a separate corpus, with longitudinal recordings, to evaluate whether the progression of the dysarthria level, according to the modified Frenchay Dysarthria Assessment (mFDA), is related to abnormal production of specific phonemes. Results: Strident, dental, pause, back, and continuant phonological classes are the ones that better explain dysarthria level progression within time-frames of at least two years, therefore allowing possible monitoring of disease progression. Conclusions: Speech is a low-cost biosignal that can be used to automatically assess PD progression. In particular, this study shows that such an assessment makes it possible to evaluate dysarthria level progression and to find which phonological classes are contributing the most to such a progression. We believe that the findings reported in this paper provide objective evidence about possible abnormalities in broader speech-related processes like respiration, therefore contributing a better understanding of the relationship between speech production patterns and other speech-related processes affected when suffering from PD. Full article
(This article belongs to the Special Issue Pathological Speech Classification and Processing for Advanced Medical Diagnosis)
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22 pages, 1759 KB  
Article
Discriminating Children with Speech Sound Disorders from Children with Typically Developing Speech Using the Motor Speech Hierarchy Probe Words: A Preliminary Analysis of Mandibular Control
by Linda Orton, Richard Palmer, Roslyn Ward, Petra Helmholz, Geoffrey R. Strauss, Paul Davey and Neville W. Hennessey
Diagnostics 2025, 15(14), 1793; https://doi.org/10.3390/diagnostics15141793 - 16 Jul 2025
Cited by 2 | Viewed by 2391
Abstract
Background/Objectives: The Motor Speech Hierarchy (MSH) Probe Words (PWs) have yet to be validated as effective in discriminating between children with impaired and children with typically developing speech motor control. This preliminary study first examined the effectiveness of the mandibular control subtest [...] Read more.
Background/Objectives: The Motor Speech Hierarchy (MSH) Probe Words (PWs) have yet to be validated as effective in discriminating between children with impaired and children with typically developing speech motor control. This preliminary study first examined the effectiveness of the mandibular control subtest of the MSH-PWs in distinguishing between typically developing (TD) and speech sound-disordered (SSD) children aged between 3 years 0 months and 3 years 6 months. Secondly, we compared automatically derived kinematic measures of jaw range and control with MSH-PW consensus scoring to assist in identifying deficits in mandibular control. Methods: Forty-one children with TD speech and 13 with SSD produced the 10 words of the mandibular stage of the MSH-PWs. A consensus team of speech pathologists observed video recordings of the words to score motor speech control and phonetic accuracy, as detailed in the MSH-PW scoring criteria. Specific measures of jaw and lip movements during speech were also extracted to derive the objective measurements, with agreement between the perceptual and objective measures of jaw range and jaw control evaluated. Results: A significant difference between TD and SSD groups was found for jaw range (p = 0.006), voicing transitions (p = 0.004) and total mandibular scores (p = 0.015). SSD and TD group discrimination was significant (at alpha = 0.01) with a balanced classification accuracy of 0.79. Initial analysis indicates objective kinematic measures using facial tracking show good agreement with perceptual judgements of jaw range and jaw control. Conclusions: The preliminary data indicate the MSH-PWs can discriminate TD speech from SSD at the level of mandibular control and can be used by clinicians to assess motor speech control. Further investigation of objective measures to support perceptual scoring is indicated. Full article
(This article belongs to the Special Issue Pathological Speech Classification and Processing for Advanced Medical Diagnosis)
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