What question did this study set out to answer?

The aim is to investigate the use of AI in analyzing speech features related to aphasia severity.

March 24, 2026Open Access

AI-Driven Speech Profiling for Aphasia: Predicting Prosodic and Phonetic Severity via Automated Disfluency Analysis

Key Points

The aim is to investigate the use of AI in analyzing speech features related to aphasia severity.
Utilized machine learning techniques for data analysis.
Identified patterns in speech disfluencies.
Employed computational approaches to evaluate phonetic and prosodic elements.
Demonstrated potential for AI in assessing speech severity.
Highlighted the effectiveness of automated analysis in identifying linguistic patterns.
Indicated that AI can contribute to better evaluation methods for aphasia.

Abstract

This work presents a study in the area of artificial intelligence applied to language-related data. The paper explores computational approaches for analyzing linguistic patterns and demonstrates the potential of machine learning techniques in this domain. This manuscript is a preprint and has not undergone peer review. It is shared to establish precedence and to facilitate early dissemination of the work. A revised version may be submitted to a peer-reviewed journal.

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Authors

Emma Al Kubaisi

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Stockholm University

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AI-Driven Speech Profiling for Aphasia: Predicting Prosodic and Phonetic Severity via Automated Disfluency Analysis

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Abstract

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Authors

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