Computational Intelligence-Based Stuttering Detection: A Systematic Review

Area of Science:

• Speech-Language Pathology
• Computer Science
• Artificial Intelligence

Background:

• Stuttering is a global speech disorder impacting communication and quality of life.
• Artificial intelligence (AI) and computational intelligence present novel opportunities for stuttering management.
• Existing research highlights the need for advanced detection and treatment methods.

Purpose of the Study:

• To systematically review recent AI and computational intelligence advancements in stuttering.
• To explore AI applications in stuttering identification and classification.
• To investigate computational intelligence's role in developing assessment tools and interventions for persons who stutter (PWS).

Main Methods:

• Systematic review of 14 peer-reviewed journal articles.
• Literature search focused on AI and computational intelligence in stuttering.
• Analysis of studies published from 2019 onward, indexed in Web of Science.

Main Results:

• AI shows promise in accurately identifying and classifying stuttering manifestations.
• Computational intelligence techniques can inform novel assessment tools and intervention strategies.
• The reviewed literature indicates a growing integration of AI in stuttering research.

Conclusions:

• AI and computational intelligence hold significant potential to revolutionize stuttering assessment and treatment.
• These technologies can enable personalized and effective approaches for persons who stutter (PWS).
• Further research and development are encouraged to enhance outcomes for PWS.