Creating a Voice Conversion Model for Estonian
Name
Hain Zuppur
Abstract
Voice conversion has a variety of uses, like enhancement of impaired speech or entertainment purposes. The main challenge in voice conversion is extracting speaker-independent linguistic features from speech. To date, one of the most promising solutions is the Cotatron model. Estonian has some high-quality speech synthesis models, but there are no voice conversion models for Estonian. This thesis aims to take the Cotatron model and train it using Estonian Text-to-Speech datasets to produce a voice conversion model for the Estonian language.
Graduation Thesis language
English
Graduation Thesis type
Bachelor - Computer Science
Supervisor(s)
Liisa Rätsep
Defence year
2021