https://scholars.lib.ntu.edu.tw/handle/123456789/580908
DC 欄位 | 值 | 語言 |
---|---|---|
dc.contributor.author | Huang T.-H | en_US |
dc.contributor.author | Lin J.-H | en_US |
dc.contributor.author | HUNG-YI LEE | en_US |
dc.creator | Huang T.-H;Lin J.-H;Lee H.-Y. | - |
dc.date.accessioned | 2021-09-02T00:05:14Z | - |
dc.date.available | 2021-09-02T00:05:14Z | - |
dc.date.issued | 2021 | - |
dc.identifier.uri | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85103941990&doi=10.1109%2fSLT48900.2021.9383498&partnerID=40&md5=6e894cbd7d659ca5df07d11ff320858a | - |
dc.identifier.uri | https://scholars.lib.ntu.edu.tw/handle/123456789/580908 | - |
dc.description.abstract | Voice conversion technologies have been greatly improved in recent years with the help of deep learning, but their capabilities of producing natural sounding utterances in different conditions remain unclear. In this paper, we gave a thorough study of the robustness of known VC models. We also modified these models, such as the replacement of speaker embeddings, to further improve their performances. We found that the sampling rate and audio duration greatly influence voice conversion. All the VC models suffer from unseen data, but AdaIN-VC is relatively more robust. Also, the speaker embedding jointly trained is more suitable for voice conversion than those trained on speaker identification. ? 2021 IEEE. | - |
dc.relation.ispartof | 2021 IEEE Spoken Language Technology Workshop, SLT 2021 - Proceedings | - |
dc.subject | Embeddings; Sampling rates; Speaker identification; Voice conversion; Deep learning | - |
dc.title | How Far Are We from Robust Voice Conversion: A Survey | en_US |
dc.type | conference paper | en |
dc.identifier.doi | 10.1109/SLT48900.2021.9383498 | - |
dc.identifier.scopus | 2-s2.0-85103941990 | - |
dc.relation.pages | 514-521 | - |
item.cerifentitytype | Publications | - |
item.fulltext | no fulltext | - |
item.openairecristype | http://purl.org/coar/resource_type/c_5794 | - |
item.openairetype | conference paper | - |
item.grantfulltext | none | - |
crisitem.author.dept | Electrical Engineering | - |
crisitem.author.dept | Intel-NTU Connected Context Computing Center | - |
crisitem.author.dept | Communication Engineering | - |
crisitem.author.dept | Computer Science and Information Engineering | - |
crisitem.author.dept | Networking and Multimedia | - |
crisitem.author.dept | Center for Artificial Intelligence and Advanced Robotics | - |
crisitem.author.dept | Master's Program in Smart Medicine and Health Informatics (SMARTMHI) | - |
crisitem.author.orcid | 0000-0002-9654-5747 | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | Others: International Research Centers | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | College of Electrical Engineering and Computer Science | - |
crisitem.author.parentorg | Others: University-Level Research Centers | - |
crisitem.author.parentorg | International College | - |
顯示於: | 電機工程學系 |
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