Abstract

Speech, as the acoustic expression of language, is one of the most natural and effective means of human information communication. With the rapid development of the Internet and communication technology, the function of robot voice interaction is more and more popular among people. However, the robotic pronunciation cannot meet people's demand for personalized voice interaction. At the same time, style transfer technology, which is widely used in image and video processing, has been relatively mature. By studying the theoretical methods of generalized style transfer technology (including the style transfer of images and video signals), and comparing and analyzing various machine learning algorithms used by the current voice style transfer technology, this paper draws the following conclusions: First, various models generally have the problem of large demand for training data and difficulty in training. Second, an algorithm model shows the alienation effect in different usage scenarios. Finally, based on the above problems, suggestions for the development of voice style transfer are put forward.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.