{"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/voice-conversion-from-unaligned-corpora-using","title":"Voice Conversion from Unaligned Corpora using Variational Autoencoding Wasserstein Generative Adversarial Networks","arxiv_id":"1704.00849","date":"2017-04-04","proceeding":null,"authors":["Chin-Cheng Hsu","Hsin-Te Hwang","Yi-Chiao Wu","Yu Tsao","Hsin-Min Wang"],"abstract":"Building a voice conversion (VC) system from non-parallel speech corpora is\nchallenging but highly valuable in real application scenarios. In most\nsituations, the source and the target speakers do not repeat the same texts or\nthey may even speak different languages. In this case, one possible, although\nindirect, solution is to build a generative model for speech. Generative models\nfocus on explaining the observations with latent variables instead of learning\na pairwise transformation function, thereby bypassing the requirement of speech\nframe alignment. In this paper, we propose a non-parallel VC framework with a\nvariational autoencoding Wasserstein generative adversarial network (VAW-GAN)\nthat explicitly considers a VC objective when building the speech model.\nExperimental results corroborate the capability of our framework for building a\nVC system from unaligned data, and demonstrate improved conversion quality.","url_abs":"http://arxiv.org/abs/1704.00849v3","url_pdf":"http://arxiv.org/pdf/1704.00849v3.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":"voice-conversion-from-unaligned-corpora-using","repo_url":"https://github.com/JeremyCCHsu/vae-npvc","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"tf","reach":null}],"tasks":[{"task_slug":null,"task_name":"Generative Adversarial Network"},{"task_slug":"voice-conversion","task_name":"Voice Conversion"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/1704.00849","atlas_url":"https://app.syntology.ai/?focus=1704.00849","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1704.00849"}},"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/JeremyCCHsu/vae-npvc","reach":null}],"summary":{"ran_draft_wrong":1},"by_repo_kind":{},"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":"793cc1c8898d8129","entry":"get_default_output","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":true,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"793cc1c8898d8129"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}