ASSISLT: Computer-aided speech therapy tool
Zuzana Bílková, Michal Bartoš, Adam Domínec, Šimon Greško, Adam Novozámský, Barbara Zitová, Markéta Paroubková · 2022 30th European Signal Processing Conference (EUSIPCO) · 2022
This work proposes a new software system ASSISLT to support speech therapy for children and adults using deep learning approaches. The application offers an adjustable set of exercises recommended by a speech therapist and aims to motivate and help with regular home practice. Augmented reality is employed to lead the exercise moves and to appraise the effort. The core of the system is automatically evaluating exercises using a webcam and developing image processing and neural network methods for face, lips, teeth, and tongue detection. The pipeline is shown together with solutions of subtasks and with demonstrations of the functionality. The statistical validation of the ASSISLT is provided, comparing the performance of speech therapy specialists and the software.