{"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/broadband-doa-estimation-using-convolutional","title":"Broadband DOA estimation using Convolutional neural networks trained with noise signals","arxiv_id":"1705.00919","date":"2017-05-02","proceeding":null,"authors":["Soumitro Chakrabarty","Emanuël. A. P. Habets"],"abstract":"A convolution neural network (CNN) based classification method for broadband\nDOA estimation is proposed, where the phase component of the short-time Fourier\ntransform coefficients of the received microphone signals are directly fed into\nthe CNN and the features required for DOA estimation are learnt during\ntraining. Since only the phase component of the input is used, the CNN can be\ntrained with synthesized noise signals, thereby making the preparation of the\ntraining data set easier compared to using speech signals. Through experimental\nevaluation, the ability of the proposed noise trained CNN framework to\ngeneralize to speech sources is demonstrated. In addition, the robustness of\nthe system to noise, small perturbations in microphone positions, as well as\nits ability to adapt to different acoustic conditions is investigated using\nexperiments with simulated and real data.","url_abs":"http://arxiv.org/abs/1705.00919v2","url_pdf":"http://arxiv.org/pdf/1705.00919v2.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":"broadband-doa-estimation-using-convolutional","repo_url":"https://github.com/Soumitro-Chakrabarty/Single-speaker-localization","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"}],"methods":[{"method_slug":"convolution","method_name":"Convolution"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1705.00919","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}