Speech Sound Disorder

Speech sound disorders (SSDs) encompass persistent difficulties in producing speech sounds, impacting intelligibility and communication. Current research focuses on developing automated diagnostic tools using machine learning, particularly deep neural networks like convolutional neural networks (CNNs) and recurrent neural networks (RNNs, such as LSTMs), to analyze acoustic features (e.g., MFCCs) and even ultrasound tongue imaging data for improved accuracy and efficiency compared to manual transcriptions. These advancements aim to streamline clinical diagnosis, personalize interventions, and enable remote monitoring of SSD progression, ultimately improving the lives of individuals with these disorders.