Pathological voice detection using joint subsapcetransfer learning

HIGHLIGHTS

  • who: X. and collaborators from the School of Optoelectronic Science and Engineering, Soochow University, Suzhou, China have published the article: Pathological Voice Detection Using Joint SubsapceTransfer Learning, in the Journal: (JOURNAL)
  • what: All this research has made a common assumption: the source data and target data are from the same database, in other words, the data from the source and target domain have the same distribution . To summarize, the main contributions of the work are as follows: A new cross-corpus pathological voice recognition framework is proposed in this paper. The aim of the JSTL . . .

     

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