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A Two-Stage Approach to Note-Level Transcription of a Specific Piano
Wang, Q (Wang, Qi); Zhou, RH (Zhou, Ruohua); Yan, YH (Yan, Yonghong)
2017
Source PublicationAPPLIED SCIENCES-BASEL
Volume7Issue:9
Abstract

This paper presents a two-stage transcription framework for a specific piano, which combines deep learning and spectrogram factorization techniques. In the first stage, two convolutional neural networks (CNNs) are adopted to recognize the notes of the piano preliminarily, and note verification for the specific individual is conducted in the second stage. The note recognition stage is independent of piano individual, in which one CNN is used to detect onsets and another is used to estimate the probabilities of pitches at each detected onset. Hence, candidate pitches at candidate onsets are obtained in the first stage. During the note verification, templates for the specific piano are generated to model the attack of note per pitch. Then, the spectrogram of the segment around candidate onset is factorized using attack templates of candidate pitches. In this way, not only the pitches are picked up by note activations, but the onsets are revised. Experiments show that CNN outperforms other types of neural networks in both onset detection and pitch estimation, and the combination of two CNNs yields better performance than a single CNN in note recognition. We also observe that note verification further improves the performance of transcription. In the transcription of a specific piano, the proposed system achieves 82% on note-wise F-measure, which outperforms the state-of-the-art.

KeywordMusic Information Retrieval Piano Transcription Note Recognition Note Verification Onset Detection Multi-pitch Estimation
DOI10.3390/app7090901
Indexed BySCI
WOS IDWOS:000414453600037
Citation statistics
Cited Times:2[WOS]   [WOS Record]     [Related Records in WOS]
Document Type期刊论文
Identifierhttp://ir.xjipc.cas.cn/handle/365002/5037
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 . A Two-Stage Approach to Note-Level Transcription of a Specific Piano[J]. APPLIED SCIENCES-BASEL,2017,7(9).
APA Wang, Q ,Zhou, RH ,&Yan, YH .(2017).A Two-Stage Approach to Note-Level Transcription of a Specific Piano.APPLIED SCIENCES-BASEL,7(9).
MLA Wang, Q ,et al."A Two-Stage Approach to Note-Level Transcription of a Specific Piano".APPLIED SCIENCES-BASEL 7.9(2017).
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