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Polyphonic Piano Transcription with a Note-Based Music Language Model
Wang, Q (Wang, Qi)[ 1,2 ]; Zhou, RH (Zhou, Ruohua)[ 1,2 ]; Yan, YH (Yan, Yonghong)[ 1,2,3 ]
2018
Source PublicationAPPLIED SCIENCES-BASEL
ISSN2076-3417
Volume8Issue:3Pages:1-15
Abstract

This paper proposes a note-based music language model (MLM) for improving note-level polyphonic piano transcription. The MLM is based on the recurrent structure, which could model the temporal correlations between notes in music sequences. To combine the outputs of the note-based MLM and acoustic model directly, an integrated architecture is adopted in this paper. We also propose an inference algorithm, in which the note-based MLM is used to predict notes at the blank onsets in the thresholding transcription results. The experimental results show that the proposed inference algorithm improves the performance of note-level transcription. We also observe that the combination of the restricted Boltzmann machine (RBM) and recurrent structure outperforms a single recurrent neural network (RNN) or long short-term memory network (LSTM) in modeling the high-dimensional note sequences. Among all the MLMs, LSTM-RBM helps the system yield the best results on all evaluation metrics regardless of the performance of acoustic models.

KeywordPolyphonic Piano Transcription Note-based Music Language Model Recurrent Neural Network Restricted Boltzmann Machine
DOI10.3390/app8030470
Indexed BySCI
WOS IDWOS:000428369400153
Citation statistics
Cited Times:1[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.xjipc.cas.cn/handle/365002/5617
Collection多语种信息技术研究室
Affiliation1.Chinese Acad Sci, Inst Acoust, Key Lab Speech Acoust & Content Understanding, Beijing 100190, Peoples R China
2.Univ Chinese Acad Sci, Beijing 100190, Peoples R China
3.Chinese Acad Sci, Xinjiang Tech Inst Phys & Chem, Xinjiang Lab Minor Speech & Language Informat Pro, Urumqi 830001, Peoples R China
Recommended Citation
GB/T 7714
Wang, Q ,Zhou, RH ,Yan, YH . Polyphonic Piano Transcription with a Note-Based Music Language Model[J]. APPLIED SCIENCES-BASEL,2018,8(3):1-15.
APA Wang, Q ,Zhou, RH ,&Yan, YH .(2018).Polyphonic Piano Transcription with a Note-Based Music Language Model.APPLIED SCIENCES-BASEL,8(3),1-15.
MLA Wang, Q ,et al."Polyphonic Piano Transcription with a Note-Based Music Language Model".APPLIED SCIENCES-BASEL 8.3(2018):1-15.
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