Transforming speech therapy for children with autism through a virtual applied behavior analysis approach - Mazlina Mamat; Marlyn Maseri; Hoe Tung Yew; Zulayti Zakaria (Quantum Academic, 2024)
Speech therapy is essential for children with Autism Spectrum Disorder (ASD), many of whom face challenges in developing functional speech and language skills. Traditional therapy approaches require significant resources and may not be accessible to all individuals in need. This gap necessitates exploring alternative, technology-assisted methods for delivering speech therapy. Although technological tools for interventions have advanced, there is still a lack of tools specifically tailored to children with ASD that integrate evidence-based behavioral therapy principles. Hence, this study developed a Virtual Speech Therapy System (VSTS) that employs Applied Behavior Analysis (ABA) principles, particularly Discrete Trial Training (DTT), within a digital framework to provide speech therapy in the Malay language. The speech therapy is established through a text-to-speech unit, a speech-recognition unit based on the Hidden Markov Model Toolkit (HTK), and a performance counter unit to measure progress. The VSTS passed the acceptance testing, and the speech-recognition unit demonstrated a promising percentage of accuracy and a relatively low word error rate during development, with 93.75% and 6.25%, respectively. It also showed a higher recognition rate for words with distinct phonetic compositions. This study contributes to the educational development of children with ASD, particularly in verbal communication through assistive technology.