Key-specific Shrinkage Techniques for Harmonic Models

Abstract

Statistical modeling of music is rapidly gaining acceptance as viable approach to a host of Music Information Retrieval related tasks, from transcription to ad hoc retrieval. As music may be viewed as an evolving pattern of notes over time, models which capture some statistical notion of sequence are preferred. The focus of this paper is on Markov models for ad hoc retrieval. In particular, we use Harmonic Models as our baseline retrieval system and explain how they may be improved by better shrinkage procedures to improve parameter estimation.