Log in

Relevant bibliographies by topics / Bidirectional Machine Translation / Journal articles

To see the other types of publications on this topic, follow the link: Bidirectional Machine Translation.

Journal articles on the topic 'Bidirectional Machine Translation'

Author: Grafiati

Published: 2 June 2025

Last updated: 31 July 2025

Create a spot-on reference in APA, MLA, Chicago, Harvard, and other styles

Select a source type:

Consult the top 50 journal articles for your research on the topic 'Bidirectional Machine Translation.'

Next to every source in the list of references, there is an 'Add to bibliography' button. Press on it, and we will generate automatically the bibliographic reference to the chosen work in the citation style you need: APA, MLA, Harvard, Chicago, Vancouver, etc.

You can also download the full text of the academic publication as pdf and read online its abstract whenever available in the metadata.

Browse journal articles on a wide variety of disciplines and organise your bibliography correctly.

1

Elisaye, Bekele Milke. "Bidirectional English to Wolaytta Machine Translation Using a Hybrid Approach." International Journal of Soft Computing and Engineering (IJSCE) 15, no. 2 (2025): 1–10. https://doi.org/10.35940/ijsce.B1028.15020525/.

Full text

Abstract:

<strong>Abstract: </strong>As a part of natural language processing (NLP), machine translation focuses on automated techniques to produce target language text from the source language text. In this study, we combined two approaches: the rule-based MT approach and the statistical MT approach. Sentence reordering, Language model, Translation models, and decoding comprise the system. POS tagging was used to reorder the sentence more comparably, the IRSTLM tool was used to create language models for English, and the Wolaytta, Giza++ tool was used for translation. To ensure mutual translation, two

APA, Harvard, Vancouver, ISO, and other styles

2

Zhou, Long, Jiajun Zhang, and Chengqing Zong. "Synchronous Bidirectional Neural Machine Translation." Transactions of the Association for Computational Linguistics 7 (November 2019): 91–105. http://dx.doi.org/10.1162/tacl_a_00256.

Full text

Abstract:

Existing approaches to neural machine translation (NMT) generate the target language sequence token-by-token from left to right. However, this kind of unidirectional decoding framework cannot make full use of the target-side future contexts which can be produced in a right-to-left decoding direction, and thus suffers from the issue of unbalanced outputs. In this paper, we introduce a synchronous bidirectional–neural machine translation (SB-NMT) that predicts its outputs using left-to-right and right-to-left decoding simultaneously and interactively, in order to leverage both of the history and

APA, Harvard, Vancouver, ISO, and other styles

3

Elisaye, Bekele Milke. "Bidirectional English to Wolaytta Machine Translation Using Hybrid Approach." International Journal of Soft Computing and Engineering (IJSCE) 15, no. 2 (2025): 1–10. https://doi.org/10.35940/ijsce.B1028.15020525.

Full text

Abstract:

<strong>Abstract:</strong> As a part of natural language processing (NLP), machine translation focuses on automated techniques to produce target language text from the source language text. In this study, we combined two approaches: the rule-based MT approach and the statistical MT approach. Sentence reordering, Language model, Translation models, and decoding comprise the system. POS tagging was used to reorder the sentence more comparably, the IRSTLM tool was used to create language models for English, and the Wolaytta, Giza++ tool was used for translation. To ensure mutual translation, two

APA, Harvard, Vancouver, ISO, and other styles

4

Karyukin, Vladislav, Diana Rakhimova, Aidana Karibayeva, Aliya Turganbayeva, and Asem Turarbek. "The neural machine translation models for the low-resource Kazakh–English language pair." PeerJ Computer Science 9 (February 8, 2023): e1224. http://dx.doi.org/10.7717/peerj-cs.1224.

Full text

Abstract:

The development of the machine translation field was driven by people’s need to communicate with each other globally by automatically translating words, sentences, and texts from one language into another. The neural machine translation approach has become one of the most significant in recent years. This approach requires large parallel corpora not available for low-resource languages, such as the Kazakh language, which makes it difficult to achieve the high performance of the neural machine translation models. This article explores the existing methods for dealing with low-resource languages

APA, Harvard, Vancouver, ISO, and other styles

5

Milke, Elisaye Bekele, Tibebe Beshah Tesema, and Mesfin Leranso Betalo. "Bidirectional English to Wolaytta Machine Translation Using a Hybrid Approach." International Journal of Soft Computing and Engineering 15, no. 2 (2025): 1–10. https://doi.org/10.35940/ijsce.b1028.15020525.

Full text

Abstract:

As a part of natural language processing (NLP), machine translation focuses on automated techniques to produce target language text from the source language text. In this study, we combined two approaches: the rule-based MT approach and the statistical MT approach. Sentence reordering, Language model, Translation models, and decoding comprise the system. POS tagging was used to reorder the sentence more comparably, the IRSTLM tool was used to create language models for English, and the Wolaytta, Giza++ tool was used for translation. To ensure mutual translation, two language models have been d

APA, Harvard, Vancouver, ISO, and other styles

6

Zhang, Zhirui, Shuangzhi Wu, Shujie Liu, Mu Li, Ming Zhou, and Tong Xu. "Regularizing Neural Machine Translation by Target-Bidirectional Agreement." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 443–50. http://dx.doi.org/10.1609/aaai.v33i01.3301443.

Full text

Abstract:

Although Neural Machine Translation (NMT) has achieved remarkable progress in the past several years, most NMT systems still suffer from a fundamental shortcoming as in other sequence generation tasks: errors made early in generation process are fed as inputs to the model and can be quickly amplified, harming subsequent sequence generation. To address this issue, we propose a novel model regularization method for NMT training, which aims to improve the agreement between translations generated by left-to-right (L2R) and right-to-left (R2L) NMT decoders. This goal is achieved by introducing two

APA, Harvard, Vancouver, ISO, and other styles

7

Yeong-Tsann, Phua, Navaratnam Sujata, Kang Chon-Moy, and Chew Wai-Seong. "Sequence-to-sequence neural machine translation for English-Malay." International Journal of Artificial Intelligence (IJ-AI) 11, no. 2 (2022): 658–65. https://doi.org/10.11591/ijai.v11.i2.pp658-665.

Full text

Abstract:

Machine translation aims to translate text from a specific language into another language using computer software. In this work, we performed neural machine translation with attention implementation on English-Malay parallel corpus. We attempt to improve the model performance by rectified linear unit (ReLU) attention alignment. Different sequence-to-sequence models were trained. These models include long-short term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (Bi-LSTM) and bidirectional GRU (Bi-GRU). In the experiment, both bidirectional models, Bi-LSTM and Bi-GRU yield a conv

APA, Harvard, Vancouver, ISO, and other styles

8

B N V Narasimha Raju, Et al. "Bidirectional LSTMs with Byte Pair Encoding in NMT for CLIR using English and Telugu Parallel Corpus." International Journal on Recent and Innovation Trends in Computing and Communication 11, no. 9 (2023): 483–89. http://dx.doi.org/10.17762/ijritcc.v11i9.8832.

Full text

Abstract:

The Neural Machine Translation (NMT) is very crucial for Cross-Lingual Information Retrieval (CLIR). NMT is effective in translating English language queries to the Telugu Language. In this paper, we are translating English queries to Telugu. The NMT will utilize a parallel corpus for translations. Telugu is a resource-poor language, it is very difficult to supply large amounts of parallel corpus to NMT. So the NMT will have a problem called Out Of Vocabulary (OOV). To overcome this problem Byte Pair Encoding (BPE) is used along with Long Short Term Memory (LSTM), which segments the rare words

APA, Harvard, Vancouver, ISO, and other styles

9

Roig Allué, Blanca. "RELIABILITY AND LIMITATIONS OF GOOGLE TRANSLATE: A BILINGUAL, BIDIRECTIONAL AND GENRE-BASED EVALUATION." Entreculturas. Revista de Traducción y Comunicación Intercultural, no. 9 (February 1, 2017): 67–80. http://dx.doi.org/10.24310/entreculturasertci.vi9.11240.

Full text

Abstract:

The popularity of machine translation systems (or CAT, computer-assisted translation), which enable their users to obtain automatically generated translations of any text, has been increasing ever since they were created. One of the most widely used machine translation is Google Translate, a statistical system whose performance is the object of study of this paper. In order to evaluate its reliability, a small-scale study has been carried out in which translations of tourist texts and football match reports published online generated by the tool have been analysed, and the most representative

APA, Harvard, Vancouver, ISO, and other styles

10

Zhao, Hongdan. "Realization of Chinese-English Bilingual Speech Dialogue System using Machine Translation Technology." Journal of Electrical Systems 20, no. 6s (2024): 1751–62. http://dx.doi.org/10.52783/jes.3093.

Full text

Abstract:

The realization of a Chinese-English bilingual speech dialogue system through machine translation technology involves developing a sophisticated system capable of seamlessly translating spoken language between Chinese and English in real-time. This system employs cutting-edge machine learning algorithms, neural networks, and natural language processing techniques to accurately interpret and translate speech inputs from one language to another. By integrating advanced speech recognition and translation models, users can engage in fluid and natural conversations across language barriers, opening

APA, Harvard, Vancouver, ISO, and other styles

11

Yonglan, Li, and He Wenjia. "English-Chinese Machine Translation Model Based on Bidirectional Neural Network with Attention Mechanism." Journal of Sensors 2022 (March 17, 2022): 1–11. http://dx.doi.org/10.1155/2022/5199248.

Full text

Abstract:

In recent years, with the development of deep learning, machine translation using neural network has gradually become the mainstream method in industry and academia. The existing Chinese-English machine translation models generally adopt the deep neural network architecture based on attention mechanism. However, it is still a challenging problem to model short and long sequences simultaneously. Therefore, a bidirectional LSTM model integrating attention mechanism is proposed. Firstly, by using the word vector as the input data of the translation model, the linguistic symbols used in the transl

APA, Harvard, Vancouver, ISO, and other styles

12

Phuoc, Nguyen Quang, Yingxiu Quan, and Cheol-Young Ock. "Building a Bidirectional English-Vietnamese Statistical Machine Translation System by Using MOSES." International Journal of Computer and Electrical Engineering 8, no. 2 (2016): 161–68. http://dx.doi.org/10.17706/ijcee.2016.8.2.161-168.

Full text

APA, Harvard, Vancouver, ISO, and other styles

13

Phua, Yeong Tsann, Sujata Navaratnam, Chon-Moy Kang, and Wai-Seong Che. "Sequence-to-sequence neural machine translation for English-Malay." IAES International Journal of Artificial Intelligence (IJ-AI) 11, no. 2 (2022): 658. http://dx.doi.org/10.11591/ijai.v11.i2.pp658-665.

Full text

Abstract:

Machine translation aims to translate text from a specific language into another language using computer software. In this work, we performed neural machine translation with attention implementation on English-Malay parallel corpus. We attempt to improve the model performance by rectified linear unit (ReLU) attention alignment. Different sequence-to-sequence models were trained. These models include long-short term memory (LSTM), gated recurrent unit (GRU), bidirectional LSTM (Bi-LSTM) and bidirectional GRU (Bi-GRU). In the experiment, both bidirectional models, Bi-LSTM and Bi-GRU yield a conv

APA, Harvard, Vancouver, ISO, and other styles

14

Dong, Jia. "Syntax-aware bidirectional decoding Neural Machine Translation model." Applied and Computational Engineering 37, no. 1 (2024): 8–15. http://dx.doi.org/10.54254/2755-2721/37/20230463.

Full text

Abstract:

The mainstream model in neural machine translation, the Transformer, relies heavily on self-attention mechanisms for translation operations. This approach has significantly improved both accuracy and speed. However, there are still some challenges. For instance, it lacks the incorporation of linguistic knowledge and the ability to leverage syntactic structure information in natural language for translation, leading to issues such as mistranslation and omission. Addressing the limitations of the Transformer's autoregressive decoding, which decodes from left to right without fully utilizing cont

APA, Harvard, Vancouver, ISO, and other styles

15

Li, Congli. "A Study on Chinese-English Machine Translation Based on Transfer Learning and Neural Networks." Wireless Communications and Mobile Computing 2022 (March 18, 2022): 1–9. http://dx.doi.org/10.1155/2022/8282164.

Full text

Abstract:

The existing Chinese-English machine translation has problems such as inaccurate word translation and difficult translation of long sentences. To this end, this paper proposes a new machine translation model based on bidirectional Chinese-English translation incorporating translation knowledge and transfer learning, and the components of this model include a recurrent neural network-based translation quality assessment model and a self-focused network-based model. The experimental results demonstrate that our method works better on the dataset of machine translation quality assessment task for

APA, Harvard, Vancouver, ISO, and other styles

16

Banat, Maysaa, and Yasmine Abu Adla. "Exploring the Effectiveness of GPT-3 in Translating Specialized Religious Text from Arabic to English: A Comparative Study with Human Translation." Journal of Translation and Language Studies 4, no. 2 (2023): 1–23. http://dx.doi.org/10.48185/jtls.v4i2.762.

Full text

Abstract:

In recent years, Natural Language Processing (NLP) models such as Generative Pre-trained Transformer 3 (GPT-3) have shown remarkable improvements in various language-related tasks, including machine translation. However, most studies that have evaluated the performance of NLP models in translation tasks have focused on general-purpose text, leaving the evaluation of their effectiveness in handling specialized text to be relatively unexplored. Therefore, this study aimed to evaluate the effectiveness of GPT-3 in translating specialized Arabic text to English and compare its performance to human

APA, Harvard, Vancouver, ISO, and other styles

17

Win, Yin Yin, and Aye Thida. "Myanmar-English Bidirectional Machine Translation System with Numerical Particles Identification." International Journal of Information Technology and Computer Science 8, no. 6 (2016): 37–43. http://dx.doi.org/10.5815/ijitcs.2016.06.05.

Full text

APA, Harvard, Vancouver, ISO, and other styles

18

Qin, Qin. "Design and Application of Chinese English Machine Translation Model Based on Improved Bidirectional Neural Network Fusion Attention Mechanism." Wireless Communications and Mobile Computing 2022 (April 22, 2022): 1–12. http://dx.doi.org/10.1155/2022/9717368.

Full text

Abstract:

In order to improve the effect of Chinese-English machine translation, this paper combines attention mechanism and neural network algorithm and applies it to Chinese-English machine learning translation. Moreover, this paper uses Gaussian distribution instead of chi-square distribution to analyze the approximate error introduced by the Chinese and English speech energy detection method. In addition, this paper studies the overall and specific approximation errors by establishing the normalized mean square error function and the absolute error function, respectively. Finally, this paper propose

APA, Harvard, Vancouver, ISO, and other styles

19

Putri, Fadia Irsania, Aji Prasetya Wibawa, and Leonel Hernandez Collante. "Refining the Performance of Indonesian-Javanese Bilingual Neural Machine Translation Using Adam Optimizer." ILKOM Jurnal Ilmiah 16, no. 3 (2024): 271–82. https://doi.org/10.33096/ilkom.v16i3.2467.271-282.

Full text

Abstract:

This study focuses on creating a Neural Machine Translation (NMT) model for Indonesian and Javanese languages using Long Short-Term Memory (LSTM) architecture. The dataset was sourced from online platforms, containing pairs of parallel sentences in both languages. Training was performed with the Adam optimizer, and its effectiveness was compared to machine translation (MT) conducted without an optimizer. The Adam optimizer was utilized to enhance the convergence speed and stabilize the model by dynamically adjusting the learning rate. Model performance was assessed using BLEU (Bilingual Evalua

APA, Harvard, Vancouver, ISO, and other styles

20

Sun, Yiqun. "Analysis of Chinese Machine Translation Training Based on Deep Learning Technology." Computational Intelligence and Neuroscience 2022 (August 2, 2022): 1–14. http://dx.doi.org/10.1155/2022/6502831.

Full text

Abstract:

With the advent of the information age, people can establish good communication through Internet technology. Mechanical translation has become a key means to solve people’s communication problems. However, there are still obstacles to communication between different languages. In order to solve this problem, this paper uses existing neural network technology to the English-Chinese bidirectional machine translation model in the field of marine science and technology. Based on deep learning technology, we collect Chinese and English abstracts and partial full texts of Chinese and English papers

APA, Harvard, Vancouver, ISO, and other styles

21

K. V. V. Satyanarayana, M. S. V. S. Bhadri Raju, B. N. V. Narasimha Raju,. "BiLSTMs and BPE for English to Telugu CLIR." Journal of Electrical Systems 20, no. 3s (2024): 2022–29. http://dx.doi.org/10.52783/jes.1798.

Full text

Abstract:

A crucial component of Cross Lingual Information Retrieval (CLIR) is Neural Machine Translation (NMT). NMT performs a good job of transforming queries in the English language into Indian languages. This study focuses on the translation of English queries into Telugu. For translations, the NMT will make use of a parallel corpus. Due to a lack of resources in the Telugu language, it is exceedingly challenging to provide NMT with sizable parallel corpora. Thus, the NMT will encounter an issue known as Out of Vocabulary (OOV). Long Short-Term Memory (LSTM) with Byte Pair Encoding (BPE), which brea

APA, Harvard, Vancouver, ISO, and other styles

22

Jaya, K., and Deepa Gupta. "Exploration of Corpus Augmentation Approach for English-Hindi Bidirectional Statistical Machine Translation System." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1059. http://dx.doi.org/10.11591/ijece.v6i3.8904.

Full text

Abstract:

Even though lot of Statistical Machine Translation(SMT) research work is happening for English-Hindi language pair, there is no effort done to standardize the dataset. Each of the research work uses different dataset, different parameters and different number of sentences during various phases of translation resulting in varied translation output. So comparing these models, understand the result of these models, to get insight into corpus behavior for these models, regenerating the result of these research work becomes tedious. This necessitates the need for standardization of dataset and to i

APA, Harvard, Vancouver, ISO, and other styles

23

Jaya, K., and Deepa Gupta. "Exploration of Corpus Augmentation Approach for English-Hindi Bidirectional Statistical Machine Translation System." International Journal of Electrical and Computer Engineering (IJECE) 6, no. 3 (2016): 1059. http://dx.doi.org/10.11591/ijece.v6i3.pp1059-1071.

Full text

Abstract:

Even though lot of Statistical Machine Translation(SMT) research work is happening for English-Hindi language pair, there is no effort done to standardize the dataset. Each of the research work uses different dataset, different parameters and different number of sentences during various phases of translation resulting in varied translation output. So comparing these models, understand the result of these models, to get insight into corpus behavior for these models, regenerating the result of these research work becomes tedious. This necessitates the need for standardization of dataset and to i

APA, Harvard, Vancouver, ISO, and other styles

24

Zayyanu, Zaki Muhammad. "Revolutionising Translation Technology: A Comparative Study of Variant Transformer Models - BERT, GPT, and T5." Computer Science & Engineering: An International Journal 14, no. 3 (2024): 15–27. http://dx.doi.org/10.5121/cseij.2024.14302.

Full text

Abstract:

Recently, transformer-based models have reshaped the landscape of Natural Language Processing (NLP), particularly in the domain of Machine Translation (MT). this study explores three revolutionary transformer models: Bidirectional Encoder Representations from Transformers (BERT), Generative Pretrained Transformer (GPT), and Text-to-Text Transfer Transformer (T5). The study delves into their architecture, capabilities, and applications in the context of translation technology. The study begins by discussing the evolution of machine translation from rule-based to statistical machine translation

APA, Harvard, Vancouver, ISO, and other styles

25

Lee, Kong-Joo, Song-Wook Lee, and Jee-Eun Kim. "A Bidirectional Korean-Japanese Statistical Machine Translation System by Using MOSES." Journal of the Korean Society of Marine Engineering 36, no. 5 (2012): 683–93. http://dx.doi.org/10.5916/jkosme.2012.36.5.683.

Full text

APA, Harvard, Vancouver, ISO, and other styles

26

Chen, Guanzheng. "Enhancing Emotional and Cultural Retention in Ancient Chinese Poetry Translation Using BERT." Asian Journal of Research in Computer Science 18, no. 5 (2025): 333–43. https://doi.org/10.9734/ajrcos/2025/v18i5659.

Full text

Abstract:

This research investigates the use of the BERT (Bidirectional Encoder Representations from Transformers) model to enhance the translation of ancient Chinese poetry into English, with particular focus on overcoming the unique challenges posed by this literary genre. Ancient Chinese poetry is renowned for its intricate rhythm, tonal variations, and dense symbolism, all deeply embedded within cultural and historical contexts. These features create significant difficulties in translation, as maintaining the original’s lyrical quality, emotional depth, and rich cultural references often proves elus

APA, Harvard, Vancouver, ISO, and other styles

27

Zuo, Guangming. "Research on the Construction of a Bidirectional Neural Network Machine Translation Model Fused with Attention Mechanism." Mathematical Problems in Engineering 2022 (August 19, 2022): 1–11. http://dx.doi.org/10.1155/2022/2971876.

Full text

Abstract:

With the development of deep learning, neural machine translation has also been paid attention and developed by researchers. Especially in the application of encoder-decoder in natural language processing, the translation performance has been significantly improved. In 2014, the attention mechanism was used in neural machine translation, the performance of translation was greatly improved, and the interpretability of the model was increased. This research proposes a research idea of sparsemax combined with AAN machine translation model and conducts multiple ablation experiments for experimenta

APA, Harvard, Vancouver, ISO, and other styles

28

Navya, D., and V. R. Nimitha. "Offline Language Translator: Breaking Communication Barriers Anywhere." International Journal of Innovative Science and Research Technology (IJISRT) 9, no. 12 (2024): 1432–34. https://doi.org/10.5281/zenodo.14558069.

Full text

Abstract:

Language barriers remain a challenge in our connected world. This project aims to develop an offline translation tool for seamless communication without  internet access. Using localized language data, pre- trained machine learning models, and natural language  processing, the app offers bidirectional translation of common phrases in multiple languages. Lightweight and user-friendly, it embeds translation algorithms directly onto devices, ensuring privacy and security. Ideal for travel, education, emergencies, and fostering inclusion, this tool promotes reliable communication and glo

APA, Harvard, Vancouver, ISO, and other styles

29

Kumar, Dr C. Srinivasa. "Two Way Sign Language Hand Gesture Translator Using Deep Learning." INTERNATIONAL JOURNAL OF SCIENTIFIC RESEARCH IN ENGINEERING AND MANAGEMENT 09, no. 06 (2025): 1–9. https://doi.org/10.55041/ijsrem50035.

Full text

Abstract:

Abstract-The Two-way Sign Language Translator is a Python-based desktop application designed to bridge communication gaps for individuals who are deaf or hard of hearing by enabling bidirectional translation between text and sign language. The system supports two primary functionalities: text-to-sign, which converts typed text into animated sign language gestures, and sign-to-text, which recognizes hand gestures captured via a webcam using a convolutional neural network (CNN). Developed with Tkinter for the graphical user interface, OpenCV for real-time video processing, Keras for machine lear

APA, Harvard, Vancouver, ISO, and other styles

30

Nouhaila, Bensalah, Ayad Habib, Adib Abdellah, and Ibn El Farouk Abdelhamid. "From recurrent neural network techniques to pre-trainedmodels: emphasis on the use in Arabic machine translation." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 2403–12. https://doi.org/10.11591/ijai.v13.i2.pp2403-2412.

Full text

Abstract:

In recent years, neural machine translation (NMT) has garnered significant attention due to its superior performance compared to traditional statistical ma-chine translation. However, NMT’s effectiveness can be limited when translating between languages with dissimilar structures, such as English and Arabic. To address this challenge, recent advances in natural language processing (NLP) have introduced unsupervised pre-training of large neural models, showing promise for enhancing various NLP tasks. This paper proposes a solution that leverages unsupervised pre-training of large neural m

APA, Harvard, Vancouver, ISO, and other styles

31

Sveta Devi, Chanambam, Loitongbam Sanayai Meetei, and Bipul Syam Purkayastha. "An empirical study on English-Mizo Statistical Machine Translation with Bible Corpus." International journal of electrical and computer engineering systems 13, no. 9 (2022): 759–65. http://dx.doi.org/10.32985/ijeces.13.9.4.

Full text

Abstract:

Machine Translation (MT) is the process of automatically converting the text or speech in one natural language to another language with the help of a machine. This work presents a Bidirectional Statistical Machine Translation (SMT) system of an extremely low resource language pair Mizo-English, built in a low resource setting. A total of 30800 sentences are collected from the English Bible dataset and manually translated to Mizo by a native linguistic expert to generate the English-Mizo parallel dataset. After subjecting to various pre-processing steps, the parallel dataset is used to build ou

APA, Harvard, Vancouver, ISO, and other styles

32

Selcuk-Simsek, Merve, and Ilyas Cicekli. "Bidirectional Machine Translation Between Turkish and Turkish Sign Language : A Data-Driven Approach." International Journal on Natural Language Computing 6, no. 3 (2017): 33–46. http://dx.doi.org/10.5121/ijnlc.2017.6303.

Full text

APA, Harvard, Vancouver, ISO, and other styles

33

Noor, TalalH. "Bidirectional English-Arabic Machine-Translation: A Model Enhancing Arabic Search for Cloud Services." Journal of Computational and Theoretical Nanoscience 14, no. 3 (2017): 1513–20. http://dx.doi.org/10.1166/jctn.2017.6470.

Full text

APA, Harvard, Vancouver, ISO, and other styles

34

Su, Jinsong, Xiangwen Zhang, Qian Lin, Yue Qin, Junfeng Yao, and Yang Liu. "Exploiting reverse target-side contexts for neural machine translation via asynchronous bidirectional decoding." Artificial Intelligence 277 (December 2019): 103168. http://dx.doi.org/10.1016/j.artint.2019.103168.

Full text

APA, Harvard, Vancouver, ISO, and other styles

35

Li, Qin. "Machine Translation of English Language Using the Complexity-Reduced Transformer Model." Mobile Information Systems 2022 (June 7, 2022): 1–5. http://dx.doi.org/10.1155/2022/6603576.

Full text

Abstract:

Previous translation models like statistical machine translation (SMT), rule-based machine translation (RBMT), hybrid machine translation (HMT), and neural machine translation (NMT) have reached their performance bottleneck. The new Transformer-based machine translation model has become the favorite choice for English language translation. For instance, Google’s BERT translation model organizes the Transformer module into bidirectional encoder representations. It is aware of the users’ search intentions as well as the material that the search engine has indexed. It does not need to evaluate pr

APA, Harvard, Vancouver, ISO, and other styles

36

Baniata, Laith H., Seyoung Park, and Seong-Bae Park. "A Multitask-Based Neural Machine Translation Model with Part-of-Speech Tags Integration for Arabic Dialects." Applied Sciences 8, no. 12 (2018): 2502. http://dx.doi.org/10.3390/app8122502.

Full text

Abstract:

The statistical machine translation for the Arabic language integrates external linguistic resources such as part-of-speech tags. The current research presents a Bidirectional Long Short-Term Memory (Bi-LSTM) - Conditional Random Fields (CRF) segment-level Arabic Dialect POS tagger model, which will be integrated into the Multitask Neural Machine Translation (NMT) model. The proposed solution for NMT is based on the recurrent neural network encoder-decoder NMT model that has been introduced recently. The study has proposed and developed a unified Multitask NMT model that shares an encoder betw

APA, Harvard, Vancouver, ISO, and other styles

37

Fan, Kai, Jiayi Wang, Bo Li, Fengming Zhou, Boxing Chen, and Luo Si. "“Bilingual Expert” Can Find Translation Errors." Proceedings of the AAAI Conference on Artificial Intelligence 33 (July 17, 2019): 6367–74. http://dx.doi.org/10.1609/aaai.v33i01.33016367.

Full text

Abstract:

The performances of machine translation (MT) systems are usually evaluated by the metric BLEU when the golden references are provided. However, in the case of model inference or production deployment, golden references are usually expensively available, such as human annotation with bilingual expertise. In order to address the issue of translation quality estimation (QE) without reference, we propose a general framework for automatic evaluation of the translation output for the QE task in the Conference on Statistical Machine Translation (WMT). We first build a conditional target language mode

APA, Harvard, Vancouver, ISO, and other styles

38

Sensors, Journal of. "Retracted: English-Chinese Machine Translation Model Based on Bidirectional Neural Network with Attention Mechanism." Journal of Sensors 2024 (January 24, 2024): 1. http://dx.doi.org/10.1155/2024/9873845.

Full text

APA, Harvard, Vancouver, ISO, and other styles

39

Hafeez, Rabab, Muhammad Waqas Anwar, Muhammad Hasan Jamal, et al. "Contextual Urdu Lemmatization Using Recurrent Neural Network Models." Mathematics 11, no. 2 (2023): 435. http://dx.doi.org/10.3390/math11020435.

Full text

Abstract:

In the field of natural language processing, machine translation is a colossally developing research area that helps humans communicate more effectively by bridging the linguistic gap. In machine translation, normalization and morphological analyses are the first and perhaps the most important modules for information retrieval (IR). To build a morphological analyzer, or to complete the normalization process, it is important to extract the correct root out of different words. Stemming and lemmatization are techniques commonly used to find the correct root words in a language. However, a few stu

APA, Harvard, Vancouver, ISO, and other styles

40

Harjo, Budi, Muljono Muljono, and Rachmad Abdullah. "Homonym and polysemy approaches with morphology extraction in weighting terms for Indonesian to English machine translation." International Journal of Electrical and Computer Engineering (IJECE) 14, no. 6 (2024): 7036. http://dx.doi.org/10.11591/ijece.v14i6.pp7036-7045.

Full text

Abstract:

Homonym and polysemy features can influence some errors in translation from a source language to another target language, for example, from Indonesian to English. A lemma or a morphology factor can cause the configuration of Indonesian homonym features. For example, the word beruang can mean an animal beruang (bear) and can mean a verb alternation ber+uang (has/have money). The Indonesian polysemy feature can also impact an error in the translation process because it can have a literal meaning and a symbolic meaning. For example, the terms bunga melati (jasmine flower) and bunga hati (lover),

APA, Harvard, Vancouver, ISO, and other styles

41

Liu, Lemao, Andrew Finch, Masao Utiyama, and Eiichiro Sumita. "Agreement on Target-Bidirectional Recurrent Neural Networks for Sequence-to-Sequence Learning." Journal of Artificial Intelligence Research 67 (March 19, 2020): 581–606. http://dx.doi.org/10.1613/jair.1.12008.

Full text

Abstract:

Recurrent neural networks are extremely appealing for sequence-to-sequence learning tasks. Despite their great success, they typically suffer from a shortcoming: they are prone to generate unbalanced targets with good prefixes but bad suffixes, and thus performance suffers when dealing with long sequences. We propose a simple yet effective approach to overcome this shortcoming. Our approach relies on the agreement between a pair of target-directional RNNs, which generates more balanced targets. In addition, we develop two efficient approximate search methods for agreement that are empirically

APA, Harvard, Vancouver, ISO, and other styles

42

Bensalah, Nouhaila, Habib Ayad, Abdellah Adib, and Abdelhamid Ibn El Farouk. "From RNN techniques to pre-trained models: emphasis on the use in Arabic machine translation." IAES International Journal of Artificial Intelligence (IJ-AI) 13, no. 2 (2024): 2403. http://dx.doi.org/10.11591/ijai.v13.i2.pp2403-2412.

Full text

Abstract:

<p>Neural Machine Translation (NMT) has gained increasing attention in recent years due to its promising performance over conventional approaches such as Statistical Machine Translation. Nevertheless, when applied to languages with different structures, such as the pair (English, Arabic) that interests us in this work, its efficiency is degraded.<br />Alternatively, the use of unsupervised pre-training of large neural models has recently made a significant leap forward in the field of Natural Language Processing (NLP). By warm starting from published checkpoints, NLP practitioners

APA, Harvard, Vancouver, ISO, and other styles

43

Zheng, Danyang. "Transfer learning-based English translation text classification in a multimedia network environment." PeerJ Computer Science 10 (January 31, 2024): e1842. http://dx.doi.org/10.7717/peerj-cs.1842.

Full text

Abstract:

In recent years, with the rapid development of the Internet and multimedia technology, English translation text classification has played an important role in various industries. However, English translation remains a complex and difficult problem. Seeking an efficient and accurate English translation method has become an urgent problem to be solved. The study first elucidated the possibility of the development of transfer learning technology in multimedia environments, which was recognized. Then, previous research on this issue, as well as the Bidirectional Encoder Representations from Transf

APA, Harvard, Vancouver, ISO, and other styles

44

Vu, Van-Hai, Quang-Phuoc Nguyen, Ebipatei Victoria Tunyan, and Cheol-Young Ock. "Improving the Performance of Vietnamese–Korean Neural Machine Translation with Contextual Embedding." Applied Sciences 11, no. 23 (2021): 11119. http://dx.doi.org/10.3390/app112311119.

Full text

Abstract:

With the recent evolution of deep learning, machine translation (MT) models and systems are being steadily improved. However, research on MT in low-resource languages such as Vietnamese and Korean is still very limited. In recent years, a state-of-the-art context-based embedding model introduced by Google, bidirectional encoder representations for transformers (BERT), has begun to appear in the neural MT (NMT) models in different ways to enhance the accuracy of MT systems. The BERT model for Vietnamese has been developed and significantly improved in natural language processing (NLP) tasks, su

APA, Harvard, Vancouver, ISO, and other styles

45

Tian, Yongli. "Syntactic complexity recognition and analysis in Chinese-English machine translation: A comparative study based on the BLSTM-CRF model." PLOS One 20, no. 6 (2025): e0325721. https://doi.org/10.1371/journal.pone.0325721.

Full text

Abstract:

To enhance the recognition and preservation of syntactic complexity in Chinese–English translation, this study proposes an optimized Bidirectional Long Short-Term Memory–Conditional Random Field (BiLSTM-CRF) model. Based on the Workshop on Machine Translation (WMT) Chinese-English parallel corpus, an experimental framework is designed for two types of specialized data: complex sentences and cross-linguistic sentence pairs. The model integrates explicit syntactic features, including part-of-speech tags, dependency relations, and syntactic tree depth, and incorporates an attention mechanism to i

APA, Harvard, Vancouver, ISO, and other styles

46

Chen, Hongli. "Identification of Grammatical Errors of English Language Based on Intelligent Translational Model." Mobile Information Systems 2022 (June 22, 2022): 1–9. http://dx.doi.org/10.1155/2022/4472190.

Full text

Abstract:

To address the problem of low kappa, precision and recall values, and high misjudgment rate in traditional methods, this study proposes an English grammatical error identification method based on a machine translation model. For this purpose, a bidirectional long short-term memory (Bi-LSTM) model is established to diagnose English grammatical errors. A machine learning (ML) model, i.e., Naive Bayes is used for the result classification of the English grammatical error diagnosis, and the N-gram model is utilized to effectively point out the location of the error. According to the preprocessing

APA, Harvard, Vancouver, ISO, and other styles

47

Li, Xiaojing. "Adoption of Wireless Network and Artificial Intelligence Algorithm in Chinese-English Tense Translation." Computational Intelligence and Neuroscience 2022 (June 11, 2022): 1–10. http://dx.doi.org/10.1155/2022/1662311.

Full text

Abstract:

In order to solve the problem of tense consistency in Chinese-English neural machine translation (NMT) system, a Chinese verb tense annotation model is proposed. Firstly, a neural network is used to build a Chinese tense annotation model. During the translation process, the source tense is passed to the target side through the alignment matrix of the traditional Attention mechanism. The probability of the candidate words inconsistent with the corresponding tense of source words in the candidate translation word set is also reduced. Then, the Chinese-English temporal annotation algorithm is int

APA, Harvard, Vancouver, ISO, and other styles

48

Chang, Daniel. "Assisting Access to COVID-19 Information Through Deep Learning Based Machine Translation: Attention Mechanism Via Bidirectional GRU." American Journal of Data Mining and Knowledge Discovery 6, no. 1 (2021): 9. http://dx.doi.org/10.11648/j.ajdmkd.20210601.12.

Full text

APA, Harvard, Vancouver, ISO, and other styles

49

Engineering, Mathematical Problems in. "Retracted: Research on the Construction of a Bidirectional Neural Network Machine Translation Model Fused with Attention Mechanism." Mathematical Problems in Engineering 2023 (August 2, 2023): 1. http://dx.doi.org/10.1155/2023/9782682.

Full text

APA, Harvard, Vancouver, ISO, and other styles

50

Behre, Piyush, Sharman Tan, Padma Varadharajan, and Shuangyu Chang. "Streaming Punctuation: A Novel Punctuation Technique Leveraging Bidirectional Context for Continuous Speech Recognition." International Journal on Natural Language Computing 11, no. 6 (2022): 01–13. http://dx.doi.org/10.5121/ijnlc.2022.11601.

Full text

Abstract:

While speech recognition Word Error Rate (WER) has reached human parity for English, continuous speech recognition scenarios such as voice typing and meeting transcriptions still suffer from segmentation and punctuation problems, resulting from irregular pausing patterns or slow speakers. Transformer sequence tagging models are effective at capturing long bi-directional context, which is crucial for automatic punctuation. Automatic Speech Recognition (ASR) production systems, however, are constrained by real-time requirements, making it hard to incorporate the right context when making punctua

APA, Harvard, Vancouver, ISO, and other styles

We offer discounts on all premium plans for authors whose works are included in thematic literature selections. Contact us to get a unique promo code!