Pitch Contour

Pitch contour analysis investigates the patterns of pitch changes in speech and music, aiming to understand how these patterns relate to linguistic meaning, musical expression, and speaker/performer characteristics. Current research employs machine learning models, such as generalized additive mixed models and convolutional neural networks, to analyze large datasets of speech and musical recordings, often focusing on the influence of context (e.g., surrounding tones, word meaning) on pitch realization. These studies contribute to a deeper understanding of human communication and musical performance, with applications ranging from improved speech synthesis and music transcription to the diagnosis of neurological conditions like Parkinson's disease.