Overview of Accent Conversion Techniques Based on Deep Learning

In modern communication, speech technology plays a vital role, with accent being one of the key features that reflects the nuances of spoken technology. However, differences in accent can make communication difficult, especially in global contexts like language learning and human computer interaction. Accent conversion approaches often solve these issues by transforming the accent of speaker to that of the other speakers, while maintaining linguistic information and speaker identity. This technology holds great applications to speech recognition, language learning, and cross-lingual communication. This paper explores the use of advanced deep learning techniques in accent conversion systems which have improved both the naturalness and intelligibility of converted speech. Additionally, we discuss the methods generally used for performance evaluation of these systems.