CRAN: An Hybrid CNN-RNN Attention-Based Model for Arabic Machine Translation

被引：12

作者：

Bensalah, Nouhaila ^{[1
]}

Ayad, Habib ^{[1
]}

Adib, Abdellah ^{[1
]}

El Farouk, Abdelhamid Ibn ^{[2
]}

机构：

[1] Univ Hassan II Casablanca, Team Networks Telecoms & Multimedia, Casablanca 20000, Morocco

[2] Teaching Languages & Cultures Lab Mohammedia, Mohammadia, Morocco

来源：

NETWORKING, INTELLIGENT SYSTEMS AND SECURITY | 2022年 / 237卷

关键词：

D O I：

10.1007/978-981-16-3637-0_7

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Machine Translation (MT) is one of the challenging tasks in the field of Natural Language Processing (NLP). The Convolutional Neural Network (CNN)-based approaches and Recurrent Neural Network (RNN)-based techniques have shown different capabilities in representing a piece of text. In this work, an hybrid CNN-RNN attention-based neural network is proposed. During training, Adam optimizer algorithm is used, and then, a popular regularization technique named dropout is applied in order to prevent some learning problems such as overfitting. The experiment results show the impact of our proposed system on the performance of Arabic machine translation.

引用

页码：87 / 102

页数：16

共 50 条

[1] CRAN: A Hybrid CNN-RNN Attention-Based Model for Text Classification
Guo, Long
Zhang, Dongxiang
Wang, Lei
Wang, Han
Cui, Bin
CONCEPTUAL MODELING, ER 2018, 2018, 11157 : 571 - 585
[2] Attention-Based CNN-RNN Arabic Text Recognition from Natural Scene Images
Butt, Hanan
Raza, Muhammad Raheel
Ramzan, Muhammad Javed
Ali, Muhammad Junaid
Haris, Muhammad
FORECASTING, 2021, 3 (03): : 520 - 540
[3] ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis
Basiri, Mohammad Ehsan
Nemati, Shahla
Abdar, Moloud
Cambria, Erik
Acharya, U. Rajendra
FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE, 2021, 115 : 279 - 294
[4] Detection and Prediction of Polycystic Ovary Syndrome Using Attention-Based CNN-RNN Classification Model
Pulluparambil, Siji Jose
Bhat, B. Subrahmanya
INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2025, 16 (02) : 687 - 700
[5] Accelerating CNN-RNN Based Machine Health Monitoring on FPGA
Feng, Xiaoyu
Yue, Jinshan
Guo, Qingwei
Yang, Huazhong
Liu, Yongpan
2019 IEEE INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE CIRCUITS AND SYSTEMS (AICAS 2019), 2019, : 184 - 188
[6] Attention-Based Combination of CNN and RNN for Relation Classification
Guo, Xiaoyu
Zhang, Hui
Liu, Rui
Ding, Xin
Tian, Runqi
Wang, Bencheng
NEURAL INFORMATION PROCESSING (ICONIP 2018), PT IV, 2018, 11304 : 244 - 255
[7] An Integrated Hybrid CNN-RNN Model for Visual Description and Generation of Captions
Khamparia, Aditya
Pandey, Babita
Tiwari, Shrasti
Gupta, Deepak
Khanna, Ashish
Rodrigues, Joel J. P. C.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING, 2020, 39 (02) : 776 - 788
[8] An OpenCL-Based Hybrid CNN-RNN Inference Accelerator On FPGA
Sun, Yunfei
Liu, Brian
Xu, Xianchao
2019 INTERNATIONAL CONFERENCE ON FIELD-PROGRAMMABLE TECHNOLOGY (ICFPT 2019), 2019, : 283 - 286
[9] Machine Fault Detection Using a Hybrid CNN-LSTM Attention-Based Model
Borre, Andressa
Seman, Laio Oriel
Camponogara, Eduardo
Stefenon, Stefano Frizzo
Mariani, Viviana Cocco
Coelho, Leandro dos Santos
SENSORS, 2023, 23 (09)
[10] A Single Attention-Based Combination of CNN and RNN for Relation Classification
Guo, Xiaoyu
Zhang, Hui
Yang, Haijun
Xu, Lianyuan
Ye, Zhiwen
IEEE ACCESS, 2019, 7 : 12467 - 12475

← 1 2 3 4 5 →