Acoustic Modelling of Drum Sounds with Hidden Markov Models for Music Transcription

This paper describes two methods for applying hidden Markov models (HMMs) to acoustic modelling of drum sound events for polyphonic music transcription. The proposed methods are instrument-wise binary modelling and modelling of instrument combinations. In the first, each target instrument is modelled with a "sound" model and all target instruments share a "silence" model. Each instrument is transcribed independently from the others. In the latter method, different instrument combinations are modelled, and an additional "silence" model is created. The proposed methods are evaluated with simulations with acoustic data, and compared with two reference methods. Simulations show that combination modelling performs better than instrument-wise modelling