Signal Processing Methods for Music Transcription is the first book dedicated to uniting
research related to signal processing algorithms and models for various aspects of music …

Research on artificial intelligence in the last two decades has greatly improved performance
of both manufacturing and service systems. Currently, there is a dire need for an article that …

Automatic music transcription is considered by many to be a key enabling technology in
music signal processing. However, the performance of transcription systems is still …

The steep rise in music downloading over CD sales has created a major shift in the music
industry away from physical media formats and towards online products and services. Music …

A method is described which analyzes the basic pattern of beats in a piece of music, the
musical meter. The analysis is performed jointly at three different time scales: at the …

Rhythm belongs with harmony, melody, and timbre as one of the most fundamental aspects
of music. Sound by its very nature is temporal, and in its most generic sense, the word …

We propose efficient particle smoothing methods for generalized state-spaces models.
Particle smoothing is an expensive O (N 2) algorithm, where N is the number of particles. We …

People naturally identify the rhythm of music as they tap their feet and sway in time with the
beat. Underlying such motions is an act of cognition that is not easily reproduced in a …

The aim of this overview is to describe methods for the automatic transcription of Western
polyphonic music. The transcription task is here understood as transforming an acoustic …

In this paper, we present a graphical model for polyphonic music transcription. Our model,
formulated as a dynamical Bayesian network, embodies a transparent and computationally …