Automatic Capture for Spectrum-Based Instrument Models

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.