{"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/diacorrect-error-correction-back-end-for","title":"DiaCorrect: Error Correction Back-end For Speaker Diarization","arxiv_id":"2309.08377","date":"2023-09-15","proceeding":null,"authors":["Jiangyu Han","Federico Landini","Johan Rohdin","Mireia Diez","Lukas Burget","Yuhang Cao","Heng Lu","Jan Cernocky"],"abstract":"In this work, we propose an error correction framework, named DiaCorrect, to refine the output of a diarization system in a simple yet effective way. This method is inspired by error correction techniques in automatic speech recognition. Our model consists of two parallel convolutional encoders and a transform-based decoder. By exploiting the interactions between the input recording and the initial system's outputs, DiaCorrect can automatically correct the initial speaker activities to minimize the diarization errors. Experiments on 2-speaker telephony data show that the proposed DiaCorrect can effectively improve the initial model's results. Our source code is publicly available at https://github.com/BUTSpeechFIT/diacorrect.","url_abs":"https://arxiv.org/abs/2309.08377v1","url_pdf":"https://arxiv.org/pdf/2309.08377v1.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":"diacorrect-error-correction-back-end-for","repo_url":"https://github.com/butspeechfit/diacorrect","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"automatic-speech-recognition-2","task_name":"Automatic Speech Recognition"},{"task_slug":"decoder","task_name":"Decoder"},{"task_slug":"speaker-diarization","task_name":"Speaker Diarization"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"speaker-diarization","task_name":"speaker-diarization"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}