Information-Theoretic Adversarial Prompt Tuning for Enhanced Non-Native Speech Recognition

Cited 0 time in webofscience Cited 0 time in scopus
  • Hit : 79
  • Download : 0
DC FieldValueLanguage
dc.contributor.authorYoon, Eunseopko
dc.contributor.authorYoon, Hee Sukko
dc.contributor.authorHarvill, Johnko
dc.contributor.authorHasegawa-Johnson, Markko
dc.contributor.authorYoo, Chang-Dongko
dc.date.accessioned2023-10-23T06:00:42Z-
dc.date.available2023-10-23T06:00:42Z-
dc.date.created2023-10-20-
dc.date.issued2023-07-
dc.identifier.citationThe 61st Annual Meeting of the Association for Computational Linguistics-
dc.identifier.urihttp://hdl.handle.net/10203/313654-
dc.languageEnglish-
dc.publisherThe 61st Annual Meeting of the Association for Computational Linguistics-
dc.titleInformation-Theoretic Adversarial Prompt Tuning for Enhanced Non-Native Speech Recognition-
dc.typeConference-
dc.type.rimsCONF-
dc.citation.publicationnameThe 61st Annual Meeting of the Association for Computational Linguistics-
dc.identifier.conferencecountryCN-
dc.identifier.conferencelocationToronto-
dc.contributor.localauthorYoo, Chang-Dong-
dc.contributor.nonIdAuthorYoon, Eunseop-
dc.contributor.nonIdAuthorYoon, Hee Suk-
dc.contributor.nonIdAuthorHarvill, John-
dc.contributor.nonIdAuthorHasegawa-Johnson, Mark-
Appears in Collection
EE-Conference Papers(학술회의논문)
Files in This Item
There are no files associated with this item.

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0