Speech Fluency

Speech fluency research aims to understand and measure the smoothness and efficiency of spoken language, focusing on both its acoustic and linguistic properties. Current research employs diverse approaches, including signal processing algorithms for automatic fluency assessment, deep learning models (like recurrent neural networks and transformers) for analyzing speech and text data, and machine learning techniques for classifying fluency levels in various populations (e.g., individuals with aphasia or dementia). These advancements offer potential for improved clinical diagnosis and treatment of speech disorders, as well as enhanced development of natural language generation systems.