{"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/emotion-detection-on-tv-show-transcripts-with","title":"Emotion Detection on TV Show Transcripts with Sequence-based Convolutional Neural Networks","arxiv_id":"1708.04299","date":"2017-08-14","proceeding":null,"authors":["Sayyed M. Zahiri","Jinho D. Choi"],"abstract":"While there have been significant advances in detecting emotions from speech\nand image recognition, emotion detection on text is still under-explored and\nremained as an active research field. This paper introduces a corpus for\ntext-based emotion detection on multiparty dialogue as well as deep neural\nmodels that outperform the existing approaches for document classification. We\nfirst present a new corpus that provides annotation of seven emotions on\nconsecutive utterances in dialogues extracted from the show, Friends. We then\nsuggest four types of sequence-based convolutional neural network models with\nattention that leverage the sequence information encapsulated in dialogue. Our\nbest model shows the accuracies of 37.9% and 54% for fine- and coarse-grained\nemotions, respectively. Given the difficulty of this task, this is promising.","url_abs":"http://arxiv.org/abs/1708.04299v1","url_pdf":"http://arxiv.org/pdf/1708.04299v1.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":"emotion-detection-on-tv-show-transcripts-with","repo_url":"https://github.com/emorynlp/character-mining","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"document-classification","task_name":"Document Classification"},{"task_slug":"classification","task_name":"General Classification"}],"methods":[],"datasets_introduced":[{"slug":"emorynlp","name":"EmoryNLP","full_name":""}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1708.04299","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}