Bird Species Identification from Bird Song

Bird Species Identification from Bird Song | 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 Short Report Bird Species Identification from Bird Song Shovon Niverd Pereira, Shaila Tajmim Anuva This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7390485/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Our project focuses on identifying bird species by detecting audio recorded bird songs. Being able to identify bird songs can be very useful from environmental safety and research perspective. This can help monitoring birds in different habitats and keep track of endangered birds. It is often difficult to identify birds manually just by observing and hearing. An automated process can ease the job hugely.Features can be extracted from bird song using different audio treatments and then classical ma- chine learning technique can be used to match them with previously trained database of birdsongs.The experimental results compare the performance obtained in different situations, encompassing the complete audio signals. Signal processing will be the main method of training and matching them with sample data. Python provides pyaudio library for capturing audio signals. Overall the process encompasses training the machine using recorded bird songs then test it against sample audios to check precision. Theoretical Computer Science Full Text Additional Declarations The authors declare no competing interests. Cite Share Download PDF Status: Posted Version 1 posted 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-7390485","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":501403347,"identity":"c1256c98-80a6-44fa-9e4a-535c3a5c3fc8","order_by":0,"name":"Shovon Niverd Pereira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA8UlEQVRIiWNgGAWjYDACZhDBBiIYGxgYKkAizA2kaDkDEmEkoIUBrgWkqw2mFw8wZ+cxfFxRdkfOvL257cPPebXR/O1ALT8qtuHUYtnMY2x45twzY5kzB5tn9m47njvjMGMDY8+Z2zi1GBxmS5NsbDucOEMisZmBd9ux3AagFmbGNrxa0n8CtdTPkH/YzPh3zrHc+YS1MB9jBGpJkJBgbGbmbajJ3UCElsOSDeeeGc7gSWxmljl2IHcjUMtBvH45f7DxY0PZHXkJ9uOPGd/U1OXOO3/44IMfFbi1QMEBGOMwKpcYLXVEKB4Fo2AUjIKRBgBA/l1xX80g/QAAAABJRU5ErkJggg==","orcid":"","institution":"Military Institute of Science and Technology","correspondingAuthor":true,"prefix":"","firstName":"Shovon","middleName":"Niverd","lastName":"Pereira","suffix":""},{"id":501403398,"identity":"f5f44a07-262a-4829-88d5-2c8309363bb8","order_by":1,"name":"Shaila Tajmim Anuva","email":"","orcid":"","institution":"Military Institute of Science and Technology","correspondingAuthor":false,"prefix":"","firstName":"Shaila","middleName":"Tajmim","lastName":"Anuva","suffix":""}],"badges":[],"createdAt":"2025-08-17 05:09:42","currentVersionCode":1,"declarations":{"humanSubjects":false,"vertebrateSubjects":false,"conflictsOfInterestStatement":false,"humanSubjectEthicalGuidelines":false,"humanSubjectConsent":false,"humanSubjectClinicalTrial":false,"humanSubjectCaseReport":false,"vertebrateSubjectEthicalGuidelines":false},"doi":"10.21203/rs.3.rs-7390485/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7390485/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":89407426,"identity":"efeead2b-c57c-46fa-b53f-0c7ff54920a1","added_by":"auto","created_at":"2025-08-19 15:28:31","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":457008,"visible":true,"origin":"","legend":"","description":"","filename":"BirdSpeciesIdentificationfromBirdSong.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7390485/v1_covered_6ce4675d-ac4d-4ff8-b622-04cbc3f56adf.pdf"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003eBird Species Identification from Bird Song\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"Military Institute of Science and Technology","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"","lastPublishedDoi":"10.21203/rs.3.rs-7390485/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7390485/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eOur project focuses on identifying bird species by detecting audio recorded bird songs. Being able to identify bird songs can be very useful from environmental safety and research perspective. This can help monitoring birds in different habitats and keep track of endangered birds. It is often difficult to identify birds manually just by observing and hearing. An automated process can ease the job hugely.Features can be extracted from bird song using different audio treatments and then classical ma- chine learning technique can be used to match them with previously trained database of birdsongs.The experimental results compare the performance obtained in different situations, encompassing the complete audio signals. Signal processing will be the main method of training and matching them with sample data. Python provides pyaudio library for capturing audio signals. Overall the process encompasses training the machine using recorded bird songs then test it against sample audios to check precision.\u003c/p\u003e","manuscriptTitle":"Bird Species Identification from Bird Song","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-19 15:12:22","doi":"10.21203/rs.3.rs-7390485/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8908ccdb-bf61-47c5-be2b-e409fd458dc7","owner":[],"postedDate":"August 19th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":53256839,"name":"Theoretical Computer Science"}],"tags":[],"updatedAt":"2025-08-19T15:12:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-19 15:12:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7390485","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7390485","identity":"rs-7390485","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}