Speech Pause

Speech pauses, the silences within spoken language, are increasingly recognized as significant indicators of various cognitive and communicative processes. Current research focuses on leveraging machine learning, particularly deep learning models like transformers and recurrent neural networks, to automatically detect, analyze, and even synthesize pauses in speech for applications ranging from improving health information delivery to diagnosing neurological disorders like Alzheimer's disease. These studies reveal that pause characteristics, including duration, placement, and type (filled vs. unfilled), offer valuable insights into speaker intent, cognitive state, and overall speech naturalness, impacting fields from speech synthesis to clinical diagnostics.