LEPOR: A Robust Evaluation Metric for Machine Translation with Augmented Factors
Code (0)
등록된 구현이 없습니다.
Tasks
Machine TranslationTranslationSimilar Papers 제목 키워드 기반
LEPOR: An Augmented Machine Translation Evaluation Metric
Machine translation (MT) was developed as one of the hottest research topics in the natural language processing (NLP) literature. One important issue in MT is that how to evaluate the MT system reasonably and tell us whe…
Machine TranslationPOSTranslationcushLEPOR: customising hLEPOR metric using Optuna for higher agreement with human judgments or pre-trained language model LaBSE
Human evaluation has always been expensive while researchers struggle to trust the automatic metrics. To address this, we propose to customise traditional metrics by taking advantages of the pre-trained language models (…
Language ModelingLanguage ModellingCANTONMT: Investigating Back-Translation and Model-Switch Mechanisms for Cantonese-English Neural Machine Translation
This paper investigates the development and evaluation of machine translation models from Cantonese to English, where we propose a novel approach to tackle low-resource language translations. The main objectives of the s…
Machine TranslationTranslationIncorporating Chinese Radicals Into Neural Machine Translation: Deeper Than Character Level
In neural machine translation (NMT), researchers face the challenge of un-seen (or out-of-vocabulary OOV) words translation. To solve this, some researchers propose the splitting of western languages such as English and …
Machine TranslationNMTTranslationDATScore: Evaluating Translation with Data Augmented Translations
The rapid development of large pretrained language models has revolutionized not only the field of Natural Language Generation (NLG) but also its evaluation. Inspired by the recent work of BARTScore: a metric leveraging …
Data AugmentationLanguage ModelingLanguage ModellingMachine Translation+2