Research on speech style transfer algorithm combined with image processing perspective

Authors

  • Yuanqi Chen

DOI:

https://doi.org/10.54097/fcis.v3i1.6032

Keywords:

Style transfer, Machine learning, Speech, Image

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.

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References

Ren Qiang. Research and application of speech style transfer technology based on Generative Adversarial Network [D]. Chongqing University of Technology,2019.

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Zhu J Y, Park T, Isola P, et al. Unpaired image-to-image translation using cycle-consistent adversarial networks[C]. Proceedings of the IEEE international conference on computer vision, 2017:2223-2232.

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Published

17-03-2023

Issue

Section

Articles

How to Cite

Chen, Y. (2023). Research on speech style transfer algorithm combined with image processing perspective. Frontiers in Computing and Intelligent Systems, 3(1), 94-96. https://doi.org/10.54097/fcis.v3i1.6032