In Western popular music, drums and percussion are an important means to emphasize and
shape the rhythm, often defining the musical style. If computers were able to analyze the …

We propose the use of Temporal Convolutional Networks for audio-based beat tracking. By
contrasting our convolutional approach with the current state-of-the-art recurrent approach …

Self-attention is an attention mechanism that learns a representation by relating different
positions in the sequence. The transformer, which is a sequence model solely based on self …

In this work, we present an end-to-end framework for audio-to-score transcription. To the
best of our knowledge, this is the first automatic music transcription approach which obtains …

We introduce the Expanded Groove MIDI dataset (E-GMD), an automatic drum transcription
(ADT) dataset that contains 444 hours of audio from 43 drum kits, making it an order of …

Fundamental frequency (f0) estimation from polyphonic music includes the tasks of multiple-
f0, melody, vocal, and bass line estimation. Historically these problems have been …

Automatic identification and professional evaluation makes musical instrument learning
more intelligent. Since a proper hand shape is the basis of fingerings in playing instruments …

Downbeat tracking consists of annotating a piece of musical audio with the estimated
position of the first beat of each bar. In recent years, increasing attention has been paid to …

Automatic drum transcription, a subtask of the more general automatic music transcription,
deals with extracting drum instrument note onsets from an audio source. Recently, progress …

We present the development and evaluation of a gamified rhythmic dictation application for
music theory learning. The application was developed as a web application in the existing …