mlsanityData to 7 Oct 2026

The Effect of Normalization for Bi-directional Amharic-English Neural Machine Translation

arXiv 2210.15224 ↗First posted 27 Oct 2022cs.CLcited by 5

Not on the map. Why?

Abstract (arXiv)

Machine translation (MT) is one of the main tasks in natural language processing whose objective is to translate texts automatically from one natural language to another. Nowadays, using deep neural networks for MT tasks has received great attention. These networks require lots of data to learn abstract representations of the input and store it in continuous vectors. This paper presents the first relatively large-scale Amharic-English parallel sentence dataset. Using these compiled data, we build bi-directional Amharic-English translation models by fine-tuning the existing Facebook M2M100 pre-trained model achieving a BLEU score of 37.79 in Amharic-English 32.74 in English-Amharic translation. Additionally, we explore the effects of Amharic homophone normalization on the machine translation task. The results show that the normalization of Amharic homophone characters increases the performance of Amharic-English machine translation in both directions.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 12 of its 36 references that are in the map. First posted on arXiv 27 Oct 2022.

Builds on

12 of 36 references.

References · 12

  1. 2017Attention Is All You Needcited by 59,932
  2. 2014Neural Machine Translation by Jointly Learning to Align and Translatecited by 4,530
  3. 2014On the Properties of Neural Machine Translation: Encoder-Decoder Approachescited by 1,303
  4. 2020Beyond English-Centric Multilingual Machine Translationcited by 559
  5. 2021Measuring and Improving Consistency in Pretrained Language Modelscited by 361
  6. 2017OpenNMT: Open-source Toolkit for Neural Machine Translationcited by 251
  7. 2018Improving the Transformer Translation Model with Document-Level Contextcited by 74
  8. 2016A Convolutional Encoder Model for Neural Machine Translationcited by 54
  9. 2020A Survey of Deep Learning Techniques for Neural Machine Translationcited by 50
  10. 2019Acquiring Knowledge from Pre-trained Model to Neural Machine Translationcited by 30
  11. 2021Extended Parallel Corpus for Amharic-English Machine Translationcited by 10
  12. 2020Evaluating Amharic Machine Translationcited by 3

Built on by

Cited by year

Citing papers per year: 2023: 4; 2024: 1.

5 papers.

  1. 2023SemEval-2023 Task 12: Sentiment Analysis for African Languages (AfriSenti-SemEval)cited by 41
  2. 2023Natural Language Processing in Ethiopian Languages: Current State, Challenges, and Opportunitiescited by 11
  3. 2024EthioLLM: Multilingual Large Language Models for Ethiopian Languages with Task Evaluationcited by 8
  4. 2023Parallel Corpus for Indigenous Language Translation: Spanish-Mazatec and Spanish-Mixteccited by 4
  5. 2023Automatic Translation of Hate Speech to Non-hate Speech in Social Media Textscited by 0