dc.contributor.author | Vahkkshshan, S | |
dc.date.accessioned | 2022-03-16T06:29:56Z | |
dc.date.available | 2022-03-16T06:29:56Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Vahkkshshan, S (2021) Augmented CycleGAN for Voice Conversion. BSc. Dissertation Informatics Institute of Technology | en_US |
dc.identifier.issn | 2017463 | |
dc.identifier.uri | http://dlib.iit.ac.lk/xmlui/handle/123456789/1005 | |
dc.description.abstract | " Voice Conversion is a subset of Voice Transformation technique that specializes in changing one speaker identity to another. Voice Conversion usually depends on parallel data or non-parallel for training data. The trouble with data is that its hard-to find proper parallel data for voice conversion training To eliminate this models based on non-parallel data was developed but even then non parallel data are hard to find as well. Therefore in this project the author will be using a CycleGAN based approach combined with a Mixup augmentation technique than can extend the data on non parallel speech corpus" | en_US |
dc.language.iso | en | en_US |
dc.subject | Mix-up Augmentation | en_US |
dc.subject | Data Augmentation | en_US |
dc.subject | CycleGAN | en_US |
dc.subject | Voice Conversion | en_US |
dc.title | Augmented CycleGAN for Voice Conversion | en_US |
dc.type | Thesis | en_US |