Neural Audio-To-Score Music Transcription For Unconstrained Polyphony Using Compact Output Representations-Reference-Cited by-同舟云学术

Neural Audio-To-Score Music Transcription For Unconstrained Polyphony Using Compact Output Representations

Published:2022-05-23 Issue: Volume: Page:
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Container-title:ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)
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Author:

Arroyo Victor¹,Valero-Mas Jose J.¹,Calvo-Zaragoza Jorge¹,Pertusa Antonio¹

Affiliation:

1. University of Alicante,University Institute for Computing Research (IUII),Spain

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9745891/9746004/09746239.pdf?arnumber=9746239

Reference17 articles.

1. An End-to-End Framework for Audio-to-Score Music Transcription on Monophonic Excerpts;román;Proc of the 19th International Society for Music Information Retrieval Conference,2018

2. Non-local musical statistics as guides for audio-to-score piano transcription

3. Joint Multi-Pitch Detection and Score Transcription for Polyphonic Piano Music

4. Data representations for audio-to-score monophonic music transcription

5. Connectionist temporal classification

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