Advancing French-to-English Machine Translation: Optimizing Attention-Driven Sequence-to-Sequence Neural Networks with Multimodal Contextual Embeddings

Authors : Md Naimul Ahsan, Mir Araf Hossain Rivin, Rakibul Islam, Md Riad Ahmed, Sharmin Sultana, Khandakar Rabbi Ahmed

Publication date : 2024/12/28

Book : International Conference on Trends in Electronics and Health Informatics

Pages : 265-280

Publisher : Springer Nature Singapore

Description : This study focuses on improving the MT by enhancing the attention-driven Seq2Seq neural networks, which is aimed at solving some of the significant hurdles in the French-to-English MT, including via contextual ambiguity, idiomatic expression, syntax complexity, gendered nouns, complex verb conjugation as well as syntax. Here, we present a new model, the sequence-aligned Transformer with CNNs, or Transformer-SA-RC, that integrates contextual features from cross-modal data streams while facilitating text-stream translation with visual, semantic, and textual data flows. Recent experiments with a high volume of phrases have been conducted based on the WMT 2014 English–French dataset that suggests significant improvements in translation quality with improvements in BLEU, ROUGE-L, and METEOR scores. The model proposed in this study was approximately 38.2% and higher than the baseline models …