Name
Abstract | ||
|---|---|---|
Well-labeled datasets available for melody extraction are scarce, which limits the further advancement of deep learning based methods. To overcome this problem, we propose to use a pitch refinement method to refine the semitone-level pitch sequences decoded from massive melody MIDI files to generate a large number of fundamental frequency (F0) values for model training. Since the refined pitch val... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/ICASSP39728.2021.9414431 | ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) |
Keywords | DocType | ISBN |
Training,Pose estimation,Training data,Signal processing algorithms,Feature extraction,Data models,Data mining | Conference | 978-1-7281-7605-5 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
6 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yongwei Gao | 1 | 0 | 0.68 |
| Xingjian Du | 2 | 1 | 3.39 |
| Bilei Zhu | 3 | 0 | 2.03 |
| Xiaoheng Sun | 4 | 0 | 0.68 |
| Wei Li | 5 | 447 | 68.94 |
| Zejun Ma | 6 | 0 | 1.01 |