Multitrack music transcription aims to transcribe a music audio input into the musical notes of
multiple instruments simultaneously. It is a very challenging task that typically requires a …

End-to-end generation of musical audio using deep learning techniques has seen an
explosion of activity recently. However, most models concentrate on generating fully mixed …

Conventional music structure analysis algorithms aim to divide a song into segments and to
group them with abstract labels (eg,'A','B', and 'C'). However, explicitly identifying the function …

We propose Beat Transformer, a novel Transformer encoder architecture for joint beat and
downbeat tracking. Different from previous models that track beats solely based on the …

We introduce Seed-Music, a suite of music generation systems capable of producing high-
quality music with fine-grained style control. Our unified framework leverages both auto …

Music source separation (MSS) aims to separate a music recording into multiple musically
distinct stems, such as vocals, bass, drums, and more. Recently, deep learning approaches …

Anomalous sound detection for machine condition monitoring or structural health monitoring
is essential in the development of Industry 4.0. However, the anomalous sounds of …

Music is characterized by complex hierarchical structures. Developing a comprehensive
model to capture these structures has been a significant challenge in the field of Music …

In music information retrieval (MIR), beat tracking is one of the most fundamental tasks. To
obtain this critical component from rhythmic music signals, a previous beat tracking system …

We propose a system for tracking beats and downbeats with two objectives: generality
across a diverse music range, and high accuracy. We achieve generality by training on …