{"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/token-level-supervised-contrastive-learning","title":"Token-Level Supervised Contrastive Learning for Punctuation Restoration","arxiv_id":"2107.09099","date":"2021-07-19","proceeding":null,"authors":["Qiushi Huang","Tom Ko","H Lilian Tang","Xubo Liu","Bo Wu"],"abstract":"Punctuation is critical in understanding natural language text. Currently, most automatic speech recognition (ASR) systems do not generate punctuation, which affects the performance of downstream tasks, such as intent detection and slot filling. This gives rise to the need for punctuation restoration. Recent work in punctuation restoration heavily utilizes pre-trained language models without considering data imbalance when predicting punctuation classes. In this work, we address this problem by proposing a token-level supervised contrastive learning method that aims at maximizing the distance of representation of different punctuation marks in the embedding space. The result shows that training with token-level supervised contrastive learning obtains up to 3.2% absolute F1 improvement on the test set.","url_abs":"https://arxiv.org/abs/2107.09099v3","url_pdf":"https://arxiv.org/pdf/2107.09099v3.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":"token-level-supervised-contrastive-learning","repo_url":"https://github.com/hqsiswiliam/punctuation-restoration-scl","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"automatic-speech-recognition-2","task_name":"Automatic Speech Recognition"},{"task_slug":"automatic-speech-recognition","task_name":"Automatic Speech Recognition (ASR)"},{"task_slug":"contrastive-learning","task_name":"Contrastive Learning"},{"task_slug":"intent-detection","task_name":"Intent Detection"},{"task_slug":"punctuation-restoration","task_name":"Punctuation Restoration"},{"task_slug":"slot-filling","task_name":"Slot Filling"},{"task_slug":"speech-recognition","task_name":"Speech Recognition"},{"task_slug":"slot-filling-1","task_name":"slot-filling"},{"task_slug":"speech-recognition-1","task_name":"speech-recognition"}],"methods":[{"method_slug":"contrastive-learning","method_name":"Contrastive Learning"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}