TY - GEN
T1 - An Effective Machine Learning Approach for English-Arabic Transliteration
AU - El-Wahab, Mohamed M.Abd
AU - Abu-Khzam, Faisal N.
AU - Den, Jamal El
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022
Y1 - 2022
N2 - Transliteration is the process of transferring a word from the alphabet of one language to the alphabet of another. The objective is to obtain a mapping from one system of writing into another, thereby helping people pronounce words and names in foreign languages and giving readers an idea of how words are pronounced by putting them in a familiar alphabet. In this paper, we explore recent trends in transliteration using deep learning models. We then adopt a convolution-networks' seq2seq model developed by Facebook for the Arabic-English transliteration problem, and compare our approach against the previous ones. Our approach builds on recent work by Google and Amazon researchers and improves on previous methods both in the training and prediction steps.
AB - Transliteration is the process of transferring a word from the alphabet of one language to the alphabet of another. The objective is to obtain a mapping from one system of writing into another, thereby helping people pronounce words and names in foreign languages and giving readers an idea of how words are pronounced by putting them in a familiar alphabet. In this paper, we explore recent trends in transliteration using deep learning models. We then adopt a convolution-networks' seq2seq model developed by Facebook for the Arabic-English transliteration problem, and compare our approach against the previous ones. Our approach builds on recent work by Google and Amazon researchers and improves on previous methods both in the training and prediction steps.
KW - Convolution networks
KW - Deep learning
KW - Transliteration
UR - http://www.scopus.com/inward/record.url?scp=85139394860&partnerID=8YFLogxK
U2 - 10.1109/ICNLP55136.2022.00063
DO - 10.1109/ICNLP55136.2022.00063
M3 - Conference Paper published in Proceedings
AN - SCOPUS:85139394860
T3 - Proceedings - 2022 4th International Conference on Natural Language Processing, ICNLP 2022
SP - 345
EP - 349
BT - Proceedings - 2022 4th International Conference on Natural Language Processing, ICNLP 2022
PB - IEEE, Institute of Electrical and Electronics Engineers
T2 - 4th International Conference on Natural Language Processing, ICNLP 2022
Y2 - 25 March 2022 through 27 March 2022
ER -