{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/deep-single-shot-musical-instrument","title":"Deep Single Shot Musical Instrument Identification using Scalograms","arxiv_id":"2108.03569","date":"2021-08-08","proceeding":null,"authors":["Debdutta Chatterjee","Arindam Dutta","Dibakar Sil","Aniruddha Chandra"],"abstract":"Musical Instrument Identification has for long had a reputation of being one of the most ill-posed problems in the field of Musical Information Retrieval(MIR). Despite several robust attempts to solve the problem, a timeline spanning over the last five odd decades, the problem remains an open conundrum. In this work, the authors take on a further complex version of the traditional problem statement. They attempt to solve the problem with minimal data available - one audio excerpt per class. We propose to use a convolutional Siamese network and a residual variant of the same to identify musical instruments based on the corresponding scalograms of their audio excerpts. Our experiments and corresponding results obtained on two publicly available datasets validate the superiority of our algorithm by $\\approx$ 3\\% over the existing synonymous algorithms in present-day literature.","url_abs":"https://arxiv.org/abs/2108.03569v1","url_pdf":"https://arxiv.org/pdf/2108.03569v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"links_only","authors_date_abstract":"arXiv metadata, CC0 1.0 (https://info.arxiv.org/help/license), from the Kaggle arXiv metadata snapshot of 2026-09-12"},"code_links":[{"paper_slug":"deep-single-shot-musical-instrument","repo_url":"https://github.com/dibakar1/deep-single-shot-musical-instrument-identificationusing-time-frequency-localized-features","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":null}],"tasks":[],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}