Multimodal Neural Machine Translation for English-Assamese Pair

被引：3

作者：

Laskar, Sahinur Rahman ^{[1
]}

Paul, Bishwaraj ^{[1
]}

Paudwal, Siddharth ^{[1
]}

Gautam, Pranjit ^{[1
]}

Biswas, Nirmita ^{[1
]}

Pakray, Partha ^{[1
]}

机构：

[1] Natl Inst Technol, Dept Comp Sci & Engn, Silchar, Assam, India

来源：

2021 INTERNATIONAL CONFERENCE ON COMPUTATIONAL PERFORMANCE EVALUATION (COMPE-2021) | 2021年

关键词：

English-Assamese; multimodal; Corpus; NMT;

D O I：

10.1109/ComPE53109.2021.9752181

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Neural machine translation is a state-of-the-art approach for the automatic translation between natural languages. The multimodal concept utilizes textual and image features for improvement in low-resource neural machine translation. There is a lack of a standard multimodal corpus for the English-Assamese low-resource pair. We present a multimodal corpus which is suitable for multimodal translation task of English-Assamese pair. The English-Assamese multimodal corpus is used to implement multimodal neural machine translation models for English-to-Assamese translation and viceversa. The comparative results of automatic evaluation metrics between text-only and multimodal neural machine translation show multimodal neural machine translation outperforms text-only neural machine translation.

引用

页码：387 / 392

页数：6