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A language-correction system tailored to the specific challenges faced by Chinese learners of English is described in the International Journal of Continuing Engineering Education and Life-Long Learning. The system combines advanced Pinyin detection and hierarchical data augmentation strategies to address long-standing issues in the accuracy and efficiency of language correction tools used by non-native English speakers.

Chinese learners of English frequently encounter issues influenced by the structure and phonetics of their native language. One of the most pressing obstacles is the misidentification of Pinyin, the romanised phonetic representation of Chinese characters. When Chinese proper nouns such as “Zhangsan” or “Beijing” are written in English, they can be erroneously flagged as spelling mistakes by existing checkers. These misclassifications disrupt the flow of writing and can mislead learners into thinking their use of these names is incorrect. Research indicates that almost two-thirds of Chinese learners encounter these kinds of errors.

The new system resolves this issue by integrating a dual-strategy Pinyin detection algorithm. It pairs syllable tree matching with linguistic rule-based methods to identify and correctly treat Pinyin terms as legitimate parts of the text. It achieves 99.95% accuracy and can process more than 5000 words per second. Such speed makes it viable for real-time use in education and the workplace.

By using hierarchical data augmentation, the same system can also highlight genuine errors in article usage, subject-verb agreement, and verb tense, aspects that are not always accounted for in the current systems. This grammar correction model uses a transformer-based architecture to treat grammar correction as a sequence-to-sequence task. It demonstrated high accuracy on datasets focused on common errors made by Chinese learners, around 85-90% for article misuse, subject-verb agreement, and verb tense issues.

English remains the lingua franca of the modern world. For millions of learners, mastering its complexities can be a daunting task. Traditional grammar checkers are often unable to account for the specific errors that arise from the structural and phonetic differences between English and the learner’s native language. This new system seeks to address that problem.

Song, L. (2026) ‘Optimisation of intelligent English grammar error correction based on multi-strategy Pinyin detection and hierarchical enhancement’, Int. J. Continuing Engineering Education and Life-Long Learning, Vol. 36, No. 8, pp.21–48.