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 …

In this paper we present a novel method for jointly extracting beats and downbeats from
audio signals. A recurrent neural network operating directly on magnitude spectrograms is …

In this paper, we undertake a critical assessment of a stateof-the-art deep neural network
approach for computational rhythm analysis. Our methodology is to deconstruct this …

As an important format of multimedia, music has filled almost everyone's life. Automatic
analyzing of music is a significant step to satisfy people's need for music retrieval and music …

Transformer is a successful deep neural network (DNN) architecture that has shown its
versatility not only in natural language processing but also in music information retrieval …

In 1999, Fujishima published" Realtime Chord Recognition of Musical Sound: a System
using Common Lisp Music". This paper kickstarted an active research topic that has been …

In this thesis we address the subject of automatic extraction of harmony information from
audio recordings. We focus on chord symbol recognition and methods for evaluating …

While global key and chord estimation for both popular and classical music recordings have
received a lot of attention, little research has been devoted to estimating the local key for …

ABSTRACT Automatic Music Transcription (AMT) is an important task in music information
retrieval. Prior work has focused on multiple fundamental frequency estimation (multi-pitch …

The continued growth of MIR is motivating more complex annotation data, consisting of
richer information, multiple annotations for a given task, and multiple tasks for a given music …