{"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/the-emotional-voices-database-towards","title":"The Emotional Voices Database: Towards Controlling the Emotion Dimension in Voice Generation Systems","arxiv_id":"1806.09514","date":"2018-06-25","proceeding":null,"authors":["Adaeze Adigwe","Noé Tits","Kevin El Haddad","Sarah Ostadabbas","Thierry Dutoit"],"abstract":"In this paper, we present a database of emotional speech intended to be\nopen-sourced and used for synthesis and generation purpose. It contains data\nfor male and female actors in English and a male actor in French. The database\ncovers 5 emotion classes so it could be suitable to build synthesis and voice\ntransformation systems with the potential to control the emotional dimension in\na continuous way. We show the data's efficiency by building a simple MLP system\nconverting neutral to angry speech style and evaluate it via a CMOS perception\ntest. Even though the system is a very simple one, the test show the efficiency\nof the data which is promising for future work.","url_abs":"http://arxiv.org/abs/1806.09514v1","url_pdf":"http://arxiv.org/pdf/1806.09514v1.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":"the-emotional-voices-database-towards","repo_url":"https://github.com/numediart/EmoV-DB","is_official":1,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"speech-emotion-recognition","task_name":"Speech Emotion Recognition"},{"task_slug":"speech-synthesis","task_name":"Speech Synthesis"},{"task_slug":"text-to-speech-synthesis","task_name":"Text-To-Speech Synthesis"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1806.09514","atlas_url":"https://app.syntology.ai/?focus=1806.09514","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1806.09514"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/numediart/EmoV-DB","reach":null}],"summary":{"unverified":1},"by_repo_kind":{"official":{"samples":1,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":1,"samples":[{"code_sha256_prefix":"571a622e2172c96d","entry":"get_start_end_from_json","repo":"numediart/EmoV-DB","repo_kind":"official","path":"align_db.py","file_url":"https://github.com/numediart/EmoV-DB/blob/HEAD/align_db.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NOASSERTION","inline_ok":false,"mcp_get_code":{"code_sha256":"571a622e2172c96d"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}