Date of Original Version
Abstract or Description
Our goal is to automate the analysis of recorded acoustic performances in order to study the relationship between scores and performance. An automated system segments a recorded performance into individual notes. These are then analyzed to determine pitch and amplitude envelopes. Spectral data is also measured. The technique consists of two stages. First, a rough estimation stage performs pitch detection based on MQ analysis. Second, an accurate estimation stage uses period-synchronous analysis. The data will ultimately be used by a machine learning process to build instrument and performance models. Experiments with trumpet tones are described.