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An end-to-end neural network for polyphonic piano music transcription
We present a supervised neural network model for polyphonic piano music transcription.
The architecture of the proposed model is analogous to speech recognition systems and …
The architecture of the proposed model is analogous to speech recognition systems and …
Variational recurrent auto-encoders
In this paper we propose a model that combines the strengths of RNNs and SGVB: the
Variational Recurrent Auto-Encoder (VRAE). Such a model can be used for efficient, large …
Variational Recurrent Auto-Encoder (VRAE). Such a model can be used for efficient, large …
Deep learning-based automatic downbeat tracking: a brief review
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 …
analyzing of music is a significant step to satisfy people's need for music retrieval and music …
Generating polyphonic music using tied parallel networks
We describe a neural network architecture which enables prediction and composition of
polyphonic music in a manner that preserves translation-invariance of the dataset …
polyphonic music in a manner that preserves translation-invariance of the dataset …
A two-stage RNN-based deep reinforcement learning approach for solving the parallel machine scheduling problem with due dates and family setups
As an essential scheduling problem with several practical applications, the parallel machine
scheduling problem (PMSP) with family setups constraints is difficult to solve and proven to …
scheduling problem (PMSP) with family setups constraints is difficult to solve and proven to …
[PDF][PDF] Drum Transcription via Joint Beat and Drum Modeling Using Convolutional Recurrent Neural Networks.
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 …
detecting drum instrument onsets but lack consideration of additional meta information like …
Polyphonic piano transcription based on graph convolutional network
The automatic music transcription (AMT) task is designed to convert raw performance audio
signals into digital representations of symbolic music for possible computational musicology …
signals into digital representations of symbolic music for possible computational musicology …
A hybrid recurrent neural network for music transcription
We investigate the problem of incorporating higher-level symbolic score-like information into
Automatic Music Transcription (AMT) systems to improve their performance. We use …
Automatic Music Transcription (AMT) systems to improve their performance. We use …
Artificial musical intelligence: A survey
Computers have been used to analyze and create music since they were first introduced in
the 1950s and 1960s. Beginning in the late 1990s, the rise of the Internet and large scale …
the 1950s and 1960s. Beginning in the late 1990s, the rise of the Internet and large scale …
Piano transcription in the studio using an extensible alternating directions framework
Given a musical audio recording, the goal of automatic music transcription is to determine a
score-like representation of the piece underlying the recording. Despite significant interest …
score-like representation of the piece underlying the recording. Despite significant interest …