Research on Intelligent English to Chinese Translation Based on Transformer Model

The application of the Transformer model represents a pivotal advancement in machine translation, owing to its utilization of a self-attention mechanism that excels particularly in the translation of extensive textual content. The primary objective of this research is to delve into and execute an English-to-Chinese translation model based on the Transformer architecture, with the intention of refining the precision and fluency of machine translation. By seamlessly integrating attention mechanisms and pre-training on extensive parallel corpora, the model adeptly captures the intricate interrelationships and subtle semantic nuances that exist between sentences. This model has exhibited superior BLEU scores and translation quality in the English-to-Chinese translation task, thereby affirming the transformative potential of the Transformer model in the domain of machine translation. This study holds considerable implications for the enhancement of cross-lingual communication efficiency and cultural exchange, while also providing invaluable insights for the continued advancement and exploration of Transformer-based translation models.