论文标题
筒仓NLP在WAT2022的参与
Silo NLP's Participation at WAT2022
论文作者
论文摘要
本文提供了对亚洲翻译研讨会（WAT2022）的“ Silo NLP”提交的系统描述。我们参加了指示多模式任务（英语 - >印地语，英语 - > Malayalam和English-> Bengali多模式翻译）。对于仅文本翻译，我们从刮擦和微调的MBART-50型号训练了变压器。对于多模式翻译，我们使用了相同的MBART架构并从图像中提取对象标签来用作与文本序列相连的视觉特征。 我们的提交提交的许多任务包括英语 - >印地语多模式翻译（评估测试），英语 - > Malayalam仅文本和多模式翻译（评估测试），英语 - > Bengali多模态翻译（挑战测试）和英语 - > bengeN-> bengeN-> Bengali - bengali文本式翻译（评估测试）。
This paper provides the system description of "Silo NLP's" submission to the Workshop on Asian Translation (WAT2022). We have participated in the Indic Multimodal tasks (English->Hindi, English->Malayalam, and English->Bengali Multimodal Translation). For text-only translation, we trained Transformers from scratch and fine-tuned mBART-50 models. For multimodal translation, we used the same mBART architecture and extracted object tags from the images to use as visual features concatenated with the text sequence. Our submission tops many tasks including English->Hindi multimodal translation (evaluation test), English->Malayalam text-only and multimodal translation (evaluation test), English->Bengali multimodal translation (challenge test), and English->Bengali text-only translation (evaluation test).
