An Accent Marking Algorithm of English Conversion System Based on Morphological Rules

Yanxia Zhao, Wei Ren, Zheng Li


Facing the English conversion system, the existing accent marking algorithms cannot acquire the morphological rules of English, making the accent marking inaccurate, inefficient, and time-consuming. To solve these problems, this paper puts forward an accent marking algorithm of English conversion system based on morphological rules. Specifically, the English audios in a self-developed English corpus were classified by the speaker classification software based on hidden Markov model, as well as audio classification technology, producing the morphological rules of English. After that, the English accents were marked by the maximum entropy model in the English conversion system. The proposed method was proved accurate and efficient in accent marking through experiments. The research results provide a good reference for marking the accents in English conversion system.

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Copyright (c) 2021 Yanxia Zhao, Wei Ren, Zheng Li

International Journal of Emerging Technologies in Learning (iJET) – eISSN: 1863-0383
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