Abstract

Currently, not all children in need of speech therapy have the opportunity to receive treatment from a therapist due to a shortage of speech-language pathologists (SLPs) worldwide. To address this issue, there is a growing demand for online tools that can assist SLPs in their daily work. The technical requirements and knowledge necessary to use these programs pose a challenge for SLPs. Furthermore, there has been a lack of systematic identification, analysis, and reporting of previous studies on this topic. We systematically reviewed OST systems that can be utilized either in clinical settings or at home as part of a comprehensive treatment program for children with speech communication disorders. We thoroughly examined the features of these programs and extracted and presented the main findings. Our analysis indicates that the majority of systems designed to support SLPs primarily utilize supervised machine learning approaches and are available as either desktop or mobile applications. The results of our review demonstrate that speech therapy systems can offer significant benefits for childhood speech disorders. To ensure the successful implementation of such systems, collaboration between computer programmers and SLPs is crucial, as it can lead to the development of effective automated programs and enable greater access to quality speech therapy for children in need.