{"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/masked-conditional-neural-networks-for-audio","title":"Masked Conditional Neural Networks for Audio Classification","arxiv_id":"1803.02421","date":"2018-03-06","proceeding":null,"authors":["Fady Medhat","David Chesmore","John Robinson"],"abstract":"We present the ConditionaL Neural Network (CLNN) and the Masked ConditionaL\nNeural Network (MCLNN) designed for temporal signal recognition. The CLNN takes\ninto consideration the temporal nature of the sound signal and the MCLNN\nextends upon the CLNN through a binary mask to preserve the spatial locality of\nthe features and allows an automated exploration of the features combination\nanalogous to hand-crafting the most relevant features for the recognition task.\nMCLNN has achieved competitive recognition accuracies on the GTZAN and the\nISMIR2004 music datasets that surpass several state-of-the-art neural network\nbased architectures and hand-crafted methods applied on both datasets.","url_abs":"http://arxiv.org/abs/1803.02421v2","url_pdf":"http://arxiv.org/pdf/1803.02421v2.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":"abstracts"},"code_links":[{"paper_slug":"masked-conditional-neural-networks-for-audio","repo_url":"https://github.com/fadymedhat/MCLNN","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":"audio-classification","task_name":"Audio Classification"},{"task_slug":"classification-1","task_name":"Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":null,"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}