Background: Intelligibility is a speaker's ability to convey a message to a listener. Including an assessment of intelligibility is essential in both research and clinical work relating to individuals with communication disorders due to speech impairment. Assessment of the intelligibility of spontaneous speech can be used as an overall indicator of the severity of a speech disorder. There is a lack of methods for measuring intelligibility on the basis of spontaneous speech.
Aims: To investigate the validity and reliability of a method where listeners transcribe understandable words and an intelligibility score is calculated on the basis of the percentage of syllables perceived as understood.
Methods & Procedures: Spontaneous speech from ten children with speech-sound disorders (mean age = 6.0 years) and ten children with typical speech and language development (mean age = 5.9 years) was recorded and presented to 20 listeners. Results were compared between the two groups and correlation with percentage of consonants correct (PCC) was examined.
Outcomes & Results: The intelligibility scores obtained correlated with PCC in single words and differed significantly between the two groups, indicating high validity. Inter-judge reliability, analysed using intra-class correlation (ICC), was excellent in terms of the average measure for several listeners.
Conclusions & Implications: The results suggest that this method can be recommended for assessing intelligibility, especially if the mean across several listeners is used. It could also be used in clinical settings when evaluating intelligibility over time, provided that the same listener makes the assessments.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/1460-6984.12067 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Preserved brain youthfulness: longitudinal evidence of slower brain aging in superagers.
Geroscience
January 2025
Department of Neurology, Ewha Womans University Mokdong Hospital, Ewha Womans University College of Medicine, Seoul, Republic of Korea.
Background: Superagers, older adults with exceptional cognitive abilities, show preserved brain structure compared to typical older adults. We investigated whether superagers have biologically younger brains based on their structural integrity.
Methods: A cohort of 153 older adults (aged 61-93) was recruited, with 63 classified as superagers based on superior episodic memory and 90 as typical older adults, of whom 64 were followed up after two years.
Assessing the Image Quality of Digitally Reconstructed Radiographs from Chest CT.
J Imaging Inform Med
January 2025
Leiden University Medical Center (LUMC), Leiden, the Netherlands.
Rising computed tomography (CT) workloads require more efficient image interpretation methods. Digitally reconstructed radiographs (DRRs), generated from CT data, may enhance workflow efficiency by enabling faster radiological assessments. Various techniques exist for generating DRRs.
View Article and Find Full Text PDFAssessing online chat-based artificial intelligence models for weight loss recommendation appropriateness and bias in the presence of guideline incongruence.
Int J Obes (Lond)
January 2025
Department of Gastroenterology and Hepatology, University of Illinois College of Medicine, Peoria, IL, USA.
Background And Aim: Managing obesity requires a comprehensive approach that involves therapeutic lifestyle changes, medications, or metabolic surgery. Many patients seek health information from online sources and artificial intelligence models like ChatGPT, Google Gemini, and Microsoft Copilot before consulting health professionals. This study aims to evaluate the appropriateness of the responses of Google Gemini and Microsoft Copilot to questions on pharmacologic and surgical management of obesity and assess for bias in their responses to either the ADA or AACE guidelines.
View Article and Find Full Text PDFUsing artificial intelligence to evaluate adherence to best practices in one anastomosis gastric bypass: first steps in a real-world setting.
Surg Endosc
January 2025
Division of General Surgery, Bariatric Unit, Tel Aviv Medical Center, Affiliated to Sackler Faculty of Medicine, Tel Aviv University, 6, Weizman St, 6423906, Tel- Aviv, Israel.
Background: Safety in one anastomosis gastric bypass (OAGB) is judged by outcomes, but it seems reasonable to utilize best practices for safety, whose performance can be evaluated and therefore improved. We aimed to test an artificial intelligence-based model in real world for the evaluation of adherence to best practices in OAGB.Please check and confirm that the authors and their respective affiliations have been correctly identified and amend if necessary.
View Article and Find Full Text PDFEvaluating AI performance in nephrology triage and subspecialty referrals.
Sci Rep
January 2025
Division of Nephrology and Hypertension, Mayo Clinic, 200 First Street SW, Rochester, MN, 55905, USA.
Artificial intelligence (AI) has shown promise in revolutionizing medical triage, particularly in the context of the rising prevalence of kidney-related conditions with the aging global population. This study evaluates the utility of ChatGPT, a large language model, in triaging nephrology cases through simulated real-world scenarios. Two nephrologists created 100 patient cases that encompassed various aspects of nephrology.
View Article and Find Full Text PDFWant AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!