Implementation of Computer-Aided Piano Music Automatic Notation Algorithm in Psychological Detoxification.
This paper analyzes the modeling of a computer-aided piano music automatic notation algorithm, combines the influence of music on psychological detachment, and designs the piano music automatic notation algorithm in psychological detachment model construction. This paper investigates the multiresolu...
| Publicado en: | Occupational Therapy International pp. 1 - 14 |
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| Autor principal: | |
| Formato: | algorithm equations & formulas research tables/charts Journal Article |
| Publicado: |
Wiley-Blackwell
6/30/2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=157741798&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 157741798 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09667903 GPF jtl: Occupational Therapy International issn: 09667903 maglogo: Y pubinfo: dt: 6/30/2022 pid: 480 pub: Wiley-Blackwell place: Malden, Massachusetts artinfo: ui: 157741798 157741798 157741798 10.1155/2022/4457167 157741798 ppf: 1 ppct: 13 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: Implementation of Computer-Aided Piano Music Automatic Notation Algorithm in Psychological Detoxification. aug: au: Zhang, Xinmei affil: School of Music, Shaanxi Normal University, Xi'an Shaanxi 710119, China sug: subj: Music Models, Psychological Music Therapy Psychological Well-Being Signal Processing, Computer Assisted Methods Occupational Therapy Data Security Human Computer Simulation Mental Disorders Therapy Algorithms Software Sound Evaluation Neural Networks (Computer) Information Technology ab: This paper analyzes the modeling of a computer-aided piano music automatic notation algorithm, combines the influence of music on psychological detachment, and designs the piano music automatic notation algorithm in psychological detachment model construction. This paper investigates the multiresolution time-frequency representation constant Q-transform (CQT), which is common in music signal analysis, and finds that although CQT has higher frequency resolution at low frequencies, it also leads to lower temporal resolution. The variable Q-transform is introduced as a tool for multibasic frequency estimation of the time-frequency representation of music signals, which has better temporal resolution than CQT at the exact frequency resolution and efficient coefficient calculation. The short-time Fourier transform and constant Q-transform time-frequency analysis methods are implemented, respectively, and note onset detection and multibasic tone detection are implemented based on CNN models. The network structure, training method, and postprocessing method of CNN are optimized. This paper proposes a temporal structure model for maintaining music coherence to avoid manual input and ensure interdependence between tracks in music generation. This paper also investigates and implements a method for generating discrete music events based on multiple channels, including a multitrack correlation model and a discretization process. In this paper, the automatic piano music notation algorithm can play an influential role in significantly enhancing the actual effect of psychological detoxification. pubtype: Academic Journal doctype: algorithm equations & formulas research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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