Neural machine translation for discourse phenomena
In recent years, Neural Machine Translation (NMT) has received increasing interest in the natural language processing field (NLP) and has achieved the state-of-the-art on numerous tasks. In this final year project, we discover how NMT models can be adapted to handle discourse phenomena in machine t...
Saved in:
Main Author: | Shen, Youlin |
---|---|
Other Authors: | Joty Shafiq Rayhan |
Format: | Final Year Project |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/144540 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
Similar Items
-
Building generalizable models for discourse phenomena evaluation and machine translation
by: Jwalapuram, Prathyusha
Published: (2023) -
Discourse structure in machine translation evaluation
by: Joty, Shafiq, et al.
Published: (2018) -
Neural machine translation with limited resources
by: Mohiuddin, Tasnim
Published: (2022) -
Improving neural machine translation: data centric approaches
by: Nguyen, Xuan Phi
Published: (2023) -
Korean jamo-level byte-pair encoding for neural machine translation
by: Lee, Junyoung
Published: (2023)