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Investigating Neural Machine Translation for Low-Resource Languages:
  Using Bavarian as a Case Study

Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case Study

12 April 2024
Wan-Hua Her
Udo Kruschwitz
ArXivPDFHTML

Papers citing "Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case Study"

4 / 4 papers shown
Title
Chunk-based Nearest Neighbor Machine Translation
Chunk-based Nearest Neighbor Machine Translation
Pedro Henrique Martins
Zita Marinho
André F.T. Martins
RALM
85
28
0
24 May 2022
AfroMT: Pretraining Strategies and Reproducible Benchmarks for
  Translation of 8 African Languages
AfroMT: Pretraining Strategies and Reproducible Benchmarks for Translation of 8 African Languages
Machel Reid
Junjie Hu
Graham Neubig
Y. Matsuo
77
31
0
10 Sep 2021
The Tatoeba Translation Challenge -- Realistic Data Sets for Low
  Resource and Multilingual MT
The Tatoeba Translation Challenge -- Realistic Data Sets for Low Resource and Multilingual MT
Jörg Tiedemann
168
165
0
13 Oct 2020
Six Challenges for Neural Machine Translation
Six Challenges for Neural Machine Translation
Philipp Koehn
Rebecca Knowles
AAML
AIMat
224
1,208
0
12 Jun 2017
1