{"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/sequence-to-sequence-generation-for-spoken","title":"Sequence-to-Sequence Generation for Spoken Dialogue via Deep Syntax Trees and Strings","arxiv_id":"1606.05491","date":"2016-06-17","proceeding":null,"authors":["Ondřej Dušek","Filip Jurčíček"],"abstract":"We present a natural language generator based on the sequence-to-sequence\napproach that can be trained to produce natural language strings as well as\ndeep syntax dependency trees from input dialogue acts, and we use it to\ndirectly compare two-step generation with separate sentence planning and\nsurface realization stages to a joint, one-step approach. We were able to train\nboth setups successfully using very little training data. The joint setup\noffers better performance, surpassing state-of-the-art with regards to\nn-gram-based scores while providing more relevant outputs.","url_abs":"http://arxiv.org/abs/1606.05491v1","url_pdf":"http://arxiv.org/pdf/1606.05491v1.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":"sequence-to-sequence-generation-for-spoken","repo_url":"https://github.com/UFAL-DSG/tgen","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"tf","reach":{"status":"unanswered"}}],"tasks":[{"task_slug":"sentence","task_name":"Sentence"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1606.05491","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}