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20172021
most citedTemporally Guided Music-to-Body-Movement Generation

40 citations · 86 across the 9 of their papers we have counts for

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Showing cs.SDShow all

5 papers · 1 filter

cs.SD20213 cited

ReconVAT: A Semi-Supervised Automatic Music Transcription Framework for Low-Resource Real-World Data

Kin Wai Cheuk, Dorien Herremans, Li Su

Most of the current supervised automatic music transcription (AMT) models lack the ability to generalize. This means that they have trouble transcribing real-world music recordings…

cs.SD20212 cited

Omnizart: A General Toolbox for Automatic Music Transcription

Yu-Te Wu, Yin-Jyun Luo, Tsung-Ping Chen +4

We present and release Omnizart, a new Python library that provides a streamlined solution to automatic music transcription (AMT). Omnizart encompasses modules that construct the l…

cs.SD2018

Play as You Like: Timbre-enhanced Multi-modal Music Style Transfer

Chien-Yu Lu, Min-Xin Xue, Chia-Che Chang +2

Style transfer of polyphonic music recordings is a challenging task when considering the modeling of diverse, imaginative, and reasonable music pieces in the style different from t…

cs.SD2018

Vocal melody extraction using patch-based CNN

Li Su

A patch-based convolutional neural network (CNN) model presented in this paper for vocal melody extraction in polyphonic music is inspired from object detection in image processing…

cs.SD20173 cited

Between Homomorphic Signal Processing and Deep Neural Networks: Constructing Deep Algorithms for Polyphonic Music Transcription

Li Su

This paper presents a new approach in understanding how deep neural networks (DNNs) work by applying homomorphic signal processing techniques. Focusing on the task of multi-pitch e…