The Effect of Spectrogram Reconstruction on Automatic Music Transcription: An Alternative Approach to Improve Transcription Accuracy
Author:
Funder
Singapore International
Agency for Science
Technology and Research (A*STAR)
MOE Tier 2
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9411940/9411911/09412155.pdf?arnumber=9412155
Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. Timbre-Trap: A Low-Resource Framework for Instrument-Agnostic Music Transcription;ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2024-04-14
2. Multi-Layer Combined Frequency and Periodicity Representations for Multi-Pitch Estimation of Multi-Instrument Music;IEEE/ACM Transactions on Audio, Speech, and Language Processing;2024
3. A U-Net Based Architecture for Automatic Music Transcription;2023 IEEE 33rd International Workshop on Machine Learning for Signal Processing (MLSP);2023-09-17
4. Onsets and Velocities: Affordable Real-Time Piano Transcription Using Convolutional Neural Networks;2023 31st European Signal Processing Conference (EUSIPCO);2023-09-04
5. MFAE: Masked frame-level autoencoder with hybrid-supervision for low-resource music transcription;2023 IEEE International Conference on Multimedia and Expo (ICME);2023-07
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