Perry R. Cook
Stanford Ctr. for Comput. Res. in Music and Acoust., CCRMA, The Knoll, Stanford Univ., Stanford, CA 94305
Dexter Morrill
Colgate Univ., Hamilton, NY 13346
Julius O. Smith
Stanford Univ., Stanford, CA 94305
Fundamental frequency detection algorithms optimized for use with instruments in the brass instrument family are presented. A new frequency tracking scheme based on adaptive periodic prediction is presented, and it is shown that this algorithm is equivalent to a high-precision adaptive comb filter. Frequency detection schemes that do not take into account the unique spectral and acoustical properties of a particular instrument family usually generate errors of three types: (1) octave and harmonic detection errors, (2) half-step errors that jitter rapidly about the true estimate, and (3) latency of detection. A frequency detection and live MIDI control system has been constructed for the trumpet, which significantly reduces detection errors and latency. By limiting the search range to the natural playing range of the trumpet, sampling rate and computation can be optimized, reducing latency in the estimates. By measuring and utilizing valve position in the frequency detection algorithm, the half-step jitter problem is completely eliminated, and latency can be further reduced. Schemes for reducing harmonic detection errors will be presented. The trumpet system as implemented will be quantitatively compared to two popularly available frequency to MIDI systems. A short demonstration of the trumpet performance system will be presented.