Visual Signatures for Music Mood and Timbre

Visual Signatures for Music Mood and Timbre | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Visual Signatures for Music Mood and Timbre Hanqin Wang, Alexei Sourin This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3999284/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Existing research on music visualization has primarily focused on creating animated visual illustrations to accompany the music being played based on fundamental attributes such as sound frequency or music structure, whereas the higher-level features, including mood and timbre, are mostly overlooked. In this paper, we propose visual signatures to describe the higher-level attributes of music, where the content and the color palette of the visual signatures are controlled by the music mood and timbre, respectively. We expect that the users with different cultural and educational backgrounds will be able to easily interpret the meaning of sound with the proposed visual signatures. In our work, we used a contrastive learning neural network for mood classification and an audio Transformer for timbre classification. The performance of the music classification models is examined by their accuracy, while multiple generated images are displayed to showcase the feasibility of visual signatures. Music Visualization Music Information Retrieval Music Classification Visual Signatures for Music Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 26 Mar, 2024 Reviews received at journal 26 Mar, 2024 Reviewers agreed at journal 05 Mar, 2024 Reviewers invited by journal 03 Mar, 2024 Editor assigned by journal 02 Mar, 2024 Submission checks completed at journal 02 Mar, 2024 First submitted to journal 29 Feb, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3999284","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276487377,"identity":"0330afcd-5e82-44b9-b69e-4b1bcfa8ff93","order_by":0,"name":"Hanqin Wang","email":"","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":false,"prefix":"","firstName":"Hanqin","middleName":"","lastName":"Wang","suffix":""},{"id":276487378,"identity":"d6b0f784-8917-4654-a57b-9b44ad5aeb09","order_by":1,"name":"Alexei Sourin","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA2ElEQVRIiWNgGAWjYPACCQZ+CIOZBC2SDcykaWFgMDhArBb+/uMPH/Puscgzvt1/TIKhwjqxgf/4BfwuupFjbMzzTKLY7M5hNgmGM+mJDRI5BfitucHDJs1zQCJx241kNgnGtsNALTwJeHXInz/+DKxl8wyQln9ALfxn8GsxOJBgBtayQQKkpQGohSH9AF4thkC/GM4BaplxI9nYIuFYunGbRA5+r8idP/7wwZsDdYn9MxIf3vhQYy3bz3/8AX49KADkCTYGHgMStEAAOym2jIJRMApGwQgAAFWORBD5K/oXAAAAAElFTkSuQmCC","orcid":"","institution":"Nanyang Technological University","correspondingAuthor":true,"prefix":"","firstName":"Alexei","middleName":"","lastName":"Sourin","suffix":""}],"badges":[],"createdAt":"2024-02-29 10:02:46","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3999284/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3999284/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52066784,"identity":"a48e0e5e-f07f-4997-bafa-3f48b29ceda3","added_by":"auto","created_at":"2024-03-06 06:56:07","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1753079,"visible":true,"origin":"","legend":"","description":"","filename":"TheVisualComputer1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3999284/v1_covered_4ab27fb8-915f-45d7-a4f9-097ad46279ff.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Visual Signatures for Music Mood and Timbre","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"the-visual-computer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"tvcj","sideBox":"Learn more about [The Visual Computer](http://link.springer.com/journal/371)","snPcode":"371","submissionUrl":"https://submission.nature.com/new-submission/371/3","title":"The Visual Computer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Music Visualization, Music Information Retrieval, Music Classification, Visual Signatures for Music","lastPublishedDoi":"10.21203/rs.3.rs-3999284/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3999284/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Existing research on music visualization has primarily focused on creating animated visual illustrations to accompany the music being played based on fundamental attributes such as sound frequency or music structure, whereas the higher-level features, including mood and timbre, are mostly overlooked. 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