In this paper, we present madmom, an open-source audio processing and music information
retrieval (MIR) library written in Python. madmom features a concise, NumPy-compatible …

Synthesize human motions from music (ie, music to dance) is appealing and has attracted
lots of research interests in recent years. It is challenging because of the requirement for …

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 present Aligned Scores and Performances (ASAP): a new dataset of 222
digital musical scores aligned with 1068 performances (more than 92 hours) of Western …

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 …

We propose a multi-task learning approach for simultaneous tempo estimation and beat
tracking of musical audio. The system shows state-of-the-art performance for both tasks on a …

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 …

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 …

In this paper we present a new tempo estimation algorithm which uses a bank of resonating
comb filters to determine the dominant periodicity of a musical excerpt. Unlike existing (comb …

Existing systems for automatic transcription of drum tracks from polyphonic music focus on
detecting drum instrument onsets but lack consideration of additional meta information like …