Developed and trained Gated-CNN models to detect types of stutter in speech and SVM classifier to suggest new therapies to the user according to his stutter type and severity
System for classifying stuttering in speech and identification of various stutter types which offers valuable support for speech therapy.
XSpeech: A Novel Deep Learning Approach to Classifying Stutters
This project aims to design and create a real-time destuttering system using audio stutter classification and speech-to-text audio cleanup to 1) create an easy speech therapy aid and 2) create the baseline for a future portable destuttering device to aid severe stammering patients in everyday life.
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