TY - JOUR
T1 - Selecting Parallel In-domain Sentences for Neural Machine Translation Using Monolingual Texts
AU - Pourmostafa Roshan Sharami, Javad
AU - Shterionov, Dimitar
AU - Spronck, Pieter
PY - 2021/12
Y1 - 2021/12
N2 - Continuously-growing data volumes lead to larger generic models. Specific use-cases are usually left out, since generic models tend to perform poorly in domain-specific cases. Our work addresses this gap with a method for selecting in-domain data from generic-domain (parallel text) corpora, for the task of machine translation. The proposed method ranks sentences in parallel general-domain data according to their cosine similarity with a monolingual domain-specific data set. We then select the top K sentences with the highest similarity score to train a new machine translation system tuned to the specific in-domain data. Our experimental results show that models trained on this in-domain data outperform models trained on generic or a mixture of generic and domain data. That is, our method selects high-quality domain-specific training instances at low computational cost and data size.
AB - Continuously-growing data volumes lead to larger generic models. Specific use-cases are usually left out, since generic models tend to perform poorly in domain-specific cases. Our work addresses this gap with a method for selecting in-domain data from generic-domain (parallel text) corpora, for the task of machine translation. The proposed method ranks sentences in parallel general-domain data according to their cosine similarity with a monolingual domain-specific data set. We then select the top K sentences with the highest similarity score to train a new machine translation system tuned to the specific in-domain data. Our experimental results show that models trained on this in-domain data outperform models trained on generic or a mixture of generic and domain data. That is, our method selects high-quality domain-specific training instances at low computational cost and data size.
KW - Machine Translation
KW - Data Selection
KW - In-domain Translation
UR - https://github.com/JoyeBright/DataSelection-NMT
UR - https://www.clinjournal.org/index.php/clinj/article/view/137
U2 - 10.26116/5eav-qz46
DO - 10.26116/5eav-qz46
M3 - Article
VL - 11
SP - 213
EP - 230
JO - Computational Linguistics in the Netherlands Journal
JF - Computational Linguistics in the Netherlands Journal
SN - 2211-4009
ER -