DC Field | Value | Language |
---|---|---|
dc.contributor.author | Park, Jiyoung | ko |
dc.contributor.author | Kim, Donghyun | ko |
dc.contributor.author | Lee, Jongpil | ko |
dc.contributor.author | Keum, Sangeun | ko |
dc.contributor.author | Nam, Juhan | ko |
dc.date.accessioned | 2019-01-23T06:05:35Z | - |
dc.date.available | 2019-01-23T06:05:35Z | - |
dc.date.created | 2018-12-19 | - |
dc.date.issued | 2018-07-14 | - |
dc.identifier.citation | International Conference on Machine Learning(ICML) | - |
dc.identifier.uri | http://hdl.handle.net/10203/249899 | - |
dc.description.abstract | Artist recognition is a task of modeling the artist’s musical style. This problem is challenging because there is no clear standard. We propose a hybrid method of the generative model i-vector and the discriminative model deep convolutional neural network. We show that this approach achieves state-of-the-art performance by complementing each other. In addition, we briefly explain the advantages and disadvantages of each approach. | - |
dc.language | English | - |
dc.publisher | The International Machine Learning Society | - |
dc.title | A Hybrid of Deep Audio Feature and i-vector for Artist Recognition | - |
dc.type | Conference | - |
dc.type.rims | CONF | - |
dc.citation.publicationname | International Conference on Machine Learning(ICML) | - |
dc.identifier.conferencecountry | SW | - |
dc.identifier.conferencelocation | Stockholm International Fairs | - |
dc.contributor.localauthor | Nam, Juhan | - |
dc.contributor.nonIdAuthor | Park, Jiyoung | - |
dc.contributor.nonIdAuthor | Kim, Donghyun | - |
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