{"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/enterprise-to-computer-star-trek-chatbot","title":"Enterprise to Computer: Star Trek chatbot","arxiv_id":"1708.00818","date":"2017-08-02","proceeding":null,"authors":["Grishma Jena","Mansi Vashisht","Abheek Basu","Lyle Ungar","João Sedoc"],"abstract":"Human interactions and human-computer interactions are strongly influenced by\nstyle as well as content. Adding a persona to a chatbot makes it more\nhuman-like and contributes to a better and more engaging user experience. In\nthis work, we propose a design for a chatbot that captures the \"style\" of Star\nTrek by incorporating references from the show along with peculiar tones of the\nfictional characters therein. Our Enterprise to Computer bot (E2Cbot) treats\nStar Trek dialog style and general dialog style differently, using two\nrecurrent neural network Encoder-Decoder models. The Star Trek dialog style\nuses sequence to sequence (SEQ2SEQ) models (Sutskever et al., 2014; Bahdanau et\nal., 2014) trained on Star Trek dialogs. The general dialog style uses Word\nGraph to shift the response of the SEQ2SEQ model into the Star Trek domain. We\nevaluate the bot both in terms of perplexity and word overlap with Star Trek\nvocabulary and subjectively using human evaluators.","url_abs":"http://arxiv.org/abs/1708.00818v1","url_pdf":"http://arxiv.org/pdf/1708.00818v1.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":"enterprise-to-computer-star-trek-chatbot","repo_url":"https://github.com/GJena/CIS-700-7_Chatbot-Project","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":null}],"tasks":[{"task_slug":"chatbot","task_name":"Chatbot"},{"task_slug":"decoder","task_name":"Decoder"}],"methods":[{"method_slug":"lstm","method_name":"LSTM"},{"method_slug":"seq2seq","method_name":"Seq2Seq"},{"method_slug":"sigmoid-activation","method_name":"Sigmoid Activation"},{"method_slug":"tanh-activation","method_name":"Tanh Activation"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}