JUMT at WMT2019 News Translation Task: A Hybrid approach to Machine Translation for Lithuanian to English

08/01/2019
by   Sainik Kumar Mahata, et al.
0

In the current work, we present a description of the system submitted to WMT 2019 News Translation Shared task. The system was created to translate news text from Lithuanian to English. To accomplish the given task, our system used a Word Embedding based Neural Machine Translation model to post edit the outputs generated by a Statistical Machine Translation model. The current paper documents the architecture of our model, descriptions of the various modules and the results produced using the same. Our system garnered a BLEU score of 17.6.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/01/2019

JUCBNMT at WMT2018 News Translation Task: Character Based Neural Machine Translation of Finnish to English

In the current work, we present a description of the system submitted to...
research
07/14/2017

LIUM Machine Translation Systems for WMT17 News Translation Task

This paper describes LIUM submissions to WMT17 News Translation Task for...
research
11/03/2019

Controlling Text Complexity in Neural Machine Translation

This work introduces a machine translation task where the output is aime...
research
10/01/2020

WeChat Neural Machine Translation Systems for WMT20

We participate in the WMT 2020 shared news translation task on Chinese t...
research
10/11/2020

Machine Translation of Mathematical Text

We have implemented a machine translation system, the PolyMath Translato...
research
10/12/2021

Evaluation of Abstractive Summarisation Models with Machine Translation in Deliberative Processes

We present work on summarising deliberative processes for non-English la...
research
09/30/2022

QUAK: A Synthetic Quality Estimation Dataset for Korean-English Neural Machine Translation

With the recent advance in neural machine translation demonstrating its ...

Please sign up or login with your details

Forgot password? Click here to reset