Machine Learning Approach to English-Afaan Oromo Text-Text Translation: Using Attention based Neural Machine Translation

Gemechu, Ebisa A.; Kanagachidambaresan, G. R.

doi:10.1109/iccct53315.2021.9711807

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Cited by 3 publications

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“…It's partly due to the lack of a suitable dataset to train the models. The situation is worse for under-resourced languages like Afaan Oromo [6] .…”

Section: Objectivementioning

confidence: 99%

Grammar-aware phrase dataset generated using a novel python package

Gemechu

Kanagachidambaresan

2023

Data in Brief

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“…It's partly due to the lack of a suitable dataset to train the models. The situation is worse for under-resourced languages like Afaan Oromo [6] .…”

Section: Objectivementioning

confidence: 99%

Grammar-aware phrase dataset generated using a novel python package

Gemechu

Kanagachidambaresan

2023

Data in Brief

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Cross-cultural English text translation strategy based on the Transformer model

Zhang

2024

Applied Mathematics and Nonlinear Sciences

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The development of science and technology makes the cooperation and cultural exchanges between various countries more and more frequent. Machine translation has the advantages of high translation efficiency and low cost, and the research devoted to machine translation has become the current trend in the cross-cultural field. Based on the application form of cross-cultural perspective transformation in English text translation, this paper proposes cross-cultural text features using the Glove model and puts forward a neuro-machine translation strategy of optimizing the Transformer model with a multi-attention mechanism, which is used to solve the task of cross-cultural English text translation. In the Chinese translation task of cross-cultural English text, the translation accuracy of the model is negatively correlated with the sequence length. The average SER is 0.551, which has good anti-confusion performance. Furthermore, it appears to have a greater lexical richness and the number of idioms used when performing the translation task. Based on this study, the proposed English text translation technique achieves better results. It can replace manual translation to accomplish complex tasks and promote the development of translation cognition.

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English-Afaan Oromo Machine Translation Using Deep Attention Neural Network

Ebisa A. Gemechu,

Kanagachidambaresan

2023

Opt. Mem. Neural Networks

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Machine Learning Approach to English-Afaan Oromo Text-Text Translation: Using Attention based Neural Machine Translation

Cited by 3 publications

References 9 publications

Grammar-aware phrase dataset generated using a novel python package

Grammar-aware phrase dataset generated using a novel python package

Cross-cultural English text translation strategy based on the Transformer model

English-Afaan Oromo Machine Translation Using Deep Attention Neural Network

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