English to Bangla Machine Translation Using Recurrent Neural Network

Siddique, Shaykh; Ahmed, Tahmid; Talukder, Md. Rifayet Azam; Uddin, Md. Mohsin

doi:10.18178/ijfcc.2020.9.2.564

Cited by 12 publications

(2 citation statements)

References 9 publications

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“…After that, some scholars put forward a way to translate the sentences produced by the new source language with the help of relevant principles according to the existing translation experience and knowledge. The language database automatically summarized in this way and the rule design can eliminate the problem of ambiguity, and the translation result is better than the rule-based machine translation [ 7 , 8 ]. Based on this, some scholars have proposed a method to locate continuous and discontinuous boundary matching according to the alignment type of fragments in the translated language sentence [ 9 ].…”

Section: Development and Current Situation Of Machine Translation Res...mentioning

confidence: 99%

English Lexical Analysis System of Machine Translation Based on Simple Recurrent Neural Network

Zhu

2022

Computational Intelligence and Neuroscience

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With the increasing communication between countries, machine translation has become an important way of communication between ethnic groups in different language systems. In order to further improve the coverage mechanism and vocabulary translation quality of the machine translation model of neural network, this paper will study the machine translation English lexical analysis system based on simple recurrent neural network. In order to improve the effect of word alignment, marking and attention mechanism are introduced into the English lexical analysis model. The experimental results show that the tagging of named entity words in the system can reduce the problem of unregistered words. Combined with the attention mechanism, it can significantly improve the effect of word alignment and label recall. It not only improves the controllability of translation but also has a positive impact on the quality of translation and its application effect in specific scenes. The evaluation of translation quality indicators shows that the system can effectively improve the accuracy and quality of Chinese-English translation.

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Section: Development and Current Situation Of Machine Translation Res...mentioning

confidence: 99%

English Lexical Analysis System of Machine Translation Based on Simple Recurrent Neural Network

Zhu

2022

Computational Intelligence and Neuroscience

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“…In contrast, MT resources on the Bangla language are very limited despite being a major language in the world, the fifth-ranked globally with 228 million native speakers and the first language of Bangladesh (Akhand et al, 2016). A number of Bangla-English MT studies are available with different methods, but they are not significant with respect to resource-rich language (Dandapat and Lewis, 2018;Hasan et al, 2019a;Siddique et al, 2021). Therefore, the aim of this study is to develop an NMT system for the Bangla-English language pair.…”

Section: Introductionmentioning

confidence: 99%

Bangla↔English Machine Translation Using Attention-based Multi-Headed Transformer Model

Dhar¹,

Roy²,

Akhand³

et al. 2021

Journal of Computer Science

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Machine Translation (MT) refers to translate texts or documents from the source language into the target language without human intervention. Any MT model is language-dependent and its development requires grammar, phrase rules, vocabulary, or relevant data for the particular language pair. Hitherto, little research on MT for Bangla-English is reported in the literature, although Bangla is a major language. This study presents a deep learning-based MT system concerning both-way translation for the Bangla-English language pair. The attention-based multi-headed transformer model has been considered in this study due to its significant features of parallelism in input processing. A transformer model consisting of encoders and decoders is adapted by tuning different parameters (especially, number of heads) to identify the best performing model for Bangla to English and vice versa. The proposed model is tested on SUPara benchmark Bangla-English corpus and evaluated the Bilingual Evaluation Understudy (BLEU) score, which is currently the most popular evaluation metric in the MT field. The proposed method is revealed as a promising Bangla-English MT system achieving BLEU scores of 21.42 and 25.44 for Bangla to English and English to Bangla MT cases, respectively.

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CVD: An Improved Approach of Software Vulnerability Detection for Object Oriented Programming Languages Using Deep Learning

Siddique

Hridoy

Khushbu

et al. 2022

Lecture Notes in Networks and Systems

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English to Bangla Machine Translation Using Recurrent Neural Network

Cited by 12 publications

References 9 publications

English Lexical Analysis System of Machine Translation Based on Simple Recurrent Neural Network

English Lexical Analysis System of Machine Translation Based on Simple Recurrent Neural Network

Bangla↔English Machine Translation Using Attention-based Multi-Headed Transformer Model

CVD: An Improved Approach of Software Vulnerability Detection for Object Oriented Programming Languages Using Deep Learning

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