Tracking rests and Tempo changes: Improved Score following with Particle filters
نویسندگان
چکیده
In this paper we present a score following system based on a Dynamic Bayesian Network, using particle filtering as inference method. The proposed model sets itself apart from existing approaches by including two new extensions: A multi-level tempo model to improve alignment quality of performances with challenging tempo changes, and an extension to reflect different expressive characteristics of notated rests. Both extensions are evaluated against a dataset of classical piano music. As the results show, the extensions improve both the accuracy and the robustness of the algorithm.
منابع مشابه
Tempo Tracking Rhythm by Sequential Monte
We present a probabilistic generative model for timing deviations in expressive music. performance. The structure of the proposed model is equivalent to a switching state space model. We formulate two well known music recognition problems, namely tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. The inferences ar...
متن کاملMonte Carlo Methods for Tempo Tracking and Rhythm Quantization
We present a probabilistic generative model for timing deviations in expressive music performance. The structure of the proposed model is equivalent to a switching state space model. The switch variables correspond to discrete note locations as in a musical score. The continuous hidden variables denote the tempo. We formulate two well known music recognition problems, namely tempo tracking and ...
متن کاملParticle Filtering Applied to Musical Tempo Tracking
This paper explores the use of particle filters for beat tracking in musical audio examples. The aim is to estimate the time-varying tempo process and to find the time locations of beats, as defined by human perception. Two alternative algorithms are presented, one which performs Rao-Blackwellisation to produce an almost deterministic formulation while the second is a formulation which models t...
متن کاملIntegrating Tempo Tracking and Quantization using Particle Filtering
We present a probabilistic switching state space model for timing deviations in expressive music performance. We formulate tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. The resulting model is suitable for real-time tempo tracking and transcription and hence useful in a number of music applications such as ada...
متن کاملTempo Induction and Beat Tracking for Audio Signals
The process of beat tracking and tempo induction can be primarily defined in terms of the concepts of tempo and beat. Tempo refers to the rate at which a musical piece is played, and is represented in score time units per real time units (beat per minute being its most popular format). A beat can be defined as a unit in a sequence of impulses which represent the tempo of a musical piece. In fac...
متن کامل