CSDL Bài trích Báo - Tạp chí
A study of data augmentation and accuracy improvement in machine translation for Vietnamese sign language
Tác giả: Thi Bich Diep Nguyen, Trung Nghia Phung, Tat Thang Vu
Số trang:
P. 143-158
Số phát hành:
Tập 39 - Số 2
Kiểu tài liệu:
Tạp chí trong nước
Nơi lưu trữ:
03 Quang Trung
Mã phân loại:
005
Ngôn ngữ:
English
Từ khóa:
Natural language processing, machine translation, Vietnamese sign language, data augmentation, data enrichment
Chủ đề:
Sign language
Tóm tắt:
In this paper, we experimented with and proposed several methods for building and improving models for the VL to VSL translation task. We presented a data augmentation method to improve the performance of our neural machine translation models. Using an initial dataset of 10k bilingual sentence pairs, we were able to obtain a new dataset of 60k sentence pairs with a perplexity score no more than 1.5 times that of the original dataset.