Automatic Music Transcription (AMT), inferring musical notes from raw audio, is a
challenging task at the core of music understanding. Unlike Automatic Speech Recognition …

Music transcription is the process of transforming recorded sound of musical performances
into symbolic representations such as sheet music or MIDI files. Extensive research and …

An ideal music synthesizer should be both interactive and expressive, generating high-
fidelity audio in realtime for arbitrary combinations of instruments and notes. Recent neural …

In the domain of Music Information Retrieval (MIR), Automatic Music Transcription (AMT)
emerges as a central challenge, aiming to convert audio signals into symbolic notations like …

We propose a unified model for three inter-related tasks: 1) to\textit {separate} individual
sound sources from a mixed music audio, 2) to\textit {transcribe} each sound source to MIDI …

Despite phenomenal progress in recent years, state-of-the-art music separation systems
produce source estimates with significant perceptual shortcomings, such as adding …

Many sounds that humans encounter are hierarchical in nature; a piano note is one of many
played during a performance, which is one of many instruments in a band, which might be …

Music source separation (MSS) aims at decomposing a music recording into its constituent
sources, such as a lead instrument and the accompaniment. Despite the difficulties in MSS …

ABSTRACT Automatic Music Transcription (AMT), in particular the problem of automatically
extracting notes from audio, has seen much recent progress via the training of neural …

Automatic music transcription (AMT) is a critical problem in the field of music information
retrieval (MIR). When AMT is faced with deep neural networks, the variety of timbres of …