A Phoneme-Informed Neural Network Model For Note-Level Singing Transcription-Reference-Cited by-同舟云学术

A Phoneme-Informed Neural Network Model For Note-Level Singing Transcription

Published:2023-06-04 Issue: Volume: Page:
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Container-title:ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Yong Sangeon¹,Su Li²,Nam Juhan¹

Affiliation:

1. KAIST,Graduate School of Culture Technology,Daejeon,Republic of Korea

2. Academia Sinica,Institute of Information Science,Taipei,Taiwan

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10094559/10094560/10096707.pdf?arnumber=10096707

Reference24 articles.

1. Learning acoustic frame labeling for speech recognition with recurrent neural networks

2. DALI: A large dataset of synchronized audio, lyrics, and notes, automatically created using teacher-student machine learning paradigm;meseguer-brocal;Proc of the 19th Int Society for Music Information Retrieval,2018

3. Connectionist temporal classification

4. Omnizart: A General Toolbox for Automatic Music Transcription

5. Enabling factorized piano music modeling and generation with the maestro dataset;hawthorne;Int Conf on Learning Representations,2019

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3. Toward Leveraging Pre-Trained Self-Supervised Frontends for Automatic Singing Voice Understanding Tasks: Three Case Studies;2023 Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC);2023-10-31