Automatic music transcription: An overview
The capability of transcribing music audio into music notation is a fascinating example of
human intelligence. It involves perception (analyzing complex auditory scenes), cognition …
human intelligence. It involves perception (analyzing complex auditory scenes), cognition …
Cross-modal music retrieval and applications: An overview of key methodologies
There has been a rapid growth of digitally available music data, including audio recordings,
digitized images of sheet music, album covers and liner notes, and video clips. This huge …
digitized images of sheet music, album covers and liner notes, and video clips. This huge …
Onsets and frames: Dual-objective piano transcription
We advance the state of the art in polyphonic piano music transcription by using a deep
convolutional and recurrent neural network which is trained to jointly predict onsets and …
convolutional and recurrent neural network which is trained to jointly predict onsets and …
Recurrent neural networks for polyphonic sound event detection in real life recordings
In this paper we present an approach to polyphonic sound event detection in real life
recordings based on bi-directional long short term memory (BLSTM) recurrent neural …
recordings based on bi-directional long short term memory (BLSTM) recurrent neural …
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 …
MT3: Multi-task multitrack music transcription
Automatic Music Transcription (AMT), inferring musical notes from raw audio, is a
challenging task at the core of music understanding. Unlike Automatic Speech Recognition …
challenging task at the core of music understanding. Unlike Automatic Speech Recognition …
Discriminatively trained recurrent neural networks for single-channel speech separation
This paper describes an in-depth investigation of training criteria, network architectures and
feature representations for regression-based single-channel speech separation with deep …
feature representations for regression-based single-channel speech separation with deep …
High-resolution piano transcription with pedals by regressing onset and offset times
Automatic music transcription (AMT) is the task of transcribing audio recordings into
symbolic representations. Recently, neural network-based methods have been applied to …
symbolic representations. Recently, neural network-based methods have been applied to …
Sequence-to-sequence piano transcription with transformers
Automatic Music Transcription has seen significant progress in recent years by training
custom deep neural networks on large datasets. However, these models have required …
custom deep neural networks on large datasets. However, these models have required …
[PDF][PDF] Deep Salience Representations for F0 Estimation in Polyphonic Music.
PowerPoint 프레젠테이션 Page 1 경영과학연구실 이태헌 2023.07.09 Deep salience
representations for f0 estimation in polyphonic music 1 Bittner, Rachel M., et al. "Deep Salience …
representations for f0 estimation in polyphonic music 1 Bittner, Rachel M., et al. "Deep Salience …