motepalli23@interspeech_2023@ISCA

Total: 1

#1 Stuttering Detection Application [PDF] [Copy] [Kimi1]

Authors: Kowshik Siva Sai Motepalli ; Vamshiraghusimha Narasinga ; Harsha Pathuri ; Hina Khan ; Sangeetha Mahesh ; Ajish K. Abraham ; Anil Kumar Vuppala

Stuttering is a prevalent speech disorder that affects millions of people worldwide. In this Show and Tell presentation, we demonstrate a novel platform that takes speech samples in English and Kannada to detect and analyze stuttering in patients. The user-friendly interface includes demographic details and speech samples, generating comprehensive reports for different stuttering disfluencies. The platform has four different user types, providing full read-only access for admins and full write access for super admins. Our platform provides valuable assistance for speech-language pathologists to evaluate speech samples. The proposed platform supports both live and recorded speech samples and presents a flexible approach to stuttering detection and analysis. Our research demonstrates the potential of technology to improve speech-language pathology for stuttering. Used F-score as a metric for evaluating the models for the stutter detection task.