Effectiveness of SpeechLP: An AI-Assisted Articulation Practice App, in Improving Speech Sound Production among Children with Speech Sound Disorders

Abstract

Speech Sound Disorders (SSDs) are prevalent childhood communication disorders that may negatively affect speech intelligibility, academic performance, and social participation. This study investigated the effectiveness of SpeechLP, an AI-assisted articulation practice application, as a supplementary intervention tool for improving speech-sound production among children with SSDs. A quasi-experimental pre-test/post-test control group design was used, involving children receiving conventional speech therapy with additional SpeechLP-based practice and children receiving conventional therapy alone. Speech-sound production accuracy, Percentage of Correct Consonants (PCC), trained target-sound accuracy, and usability perceptions were assessed. The findings demonstrated that SpeechLP-supported practice was associated with greater improvements in speech-sound accuracy and target-sound production compared with conventional therapy alone. Positive usability ratings from parents and/or speech-language pathologists further indicated that SpeechLP was an acceptable and practical supplementary tool. These findings highlight the potential of AI-assisted digital interventions to enhance pediatric speech-language therapy.