@inproceedings{alqaisi-okeefe-2019-en,
title = "En-Ar Bilingual Word Embeddings without Word Alignment: Factors Effects",
author = "Alqaisi, Taghreed and
O{'}Keefe, Simon",
editor = "El-Hajj, Wassim and
Belguith, Lamia Hadrich and
Bougares, Fethi and
Magdy, Walid and
Zitouni, Imed and
Tomeh, Nadi and
El-Haj, Mahmoud and
Zaghouani, Wajdi",
booktitle = "Proceedings of the Fourth Arabic Natural Language Processing Workshop",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-4611",
doi = "10.18653/v1/W19-4611",
pages = "97--107",
abstract = "This paper introduces the first attempt to investigate morphological segmentation on En-Ar bilingual word embeddings using bilingual word embeddings model without word alignment (BilBOWA). We investigate the effect of sentence length and embedding size on the learning process. Our experiment shows that using the D3 segmentation scheme improves the accuracy of learning bilingual word embeddings up to 10 percentage points compared to the ATB and D0 schemes in all different training settings.",
}
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<abstract>This paper introduces the first attempt to investigate morphological segmentation on En-Ar bilingual word embeddings using bilingual word embeddings model without word alignment (BilBOWA). We investigate the effect of sentence length and embedding size on the learning process. Our experiment shows that using the D3 segmentation scheme improves the accuracy of learning bilingual word embeddings up to 10 percentage points compared to the ATB and D0 schemes in all different training settings.</abstract>
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%0 Conference Proceedings
%T En-Ar Bilingual Word Embeddings without Word Alignment: Factors Effects
%A Alqaisi, Taghreed
%A O’Keefe, Simon
%Y El-Hajj, Wassim
%Y Belguith, Lamia Hadrich
%Y Bougares, Fethi
%Y Magdy, Walid
%Y Zitouni, Imed
%Y Tomeh, Nadi
%Y El-Haj, Mahmoud
%Y Zaghouani, Wajdi
%S Proceedings of the Fourth Arabic Natural Language Processing Workshop
%D 2019
%8 August
%I Association for Computational Linguistics
%C Florence, Italy
%F alqaisi-okeefe-2019-en
%X This paper introduces the first attempt to investigate morphological segmentation on En-Ar bilingual word embeddings using bilingual word embeddings model without word alignment (BilBOWA). We investigate the effect of sentence length and embedding size on the learning process. Our experiment shows that using the D3 segmentation scheme improves the accuracy of learning bilingual word embeddings up to 10 percentage points compared to the ATB and D0 schemes in all different training settings.
%R 10.18653/v1/W19-4611
%U https://aclanthology.org/W19-4611
%U https://doi.org/10.18653/v1/W19-4611
%P 97-107
Markdown (Informal)
[En-Ar Bilingual Word Embeddings without Word Alignment: Factors Effects](https://aclanthology.org/W19-4611) (Alqaisi & O’Keefe, WANLP 2019)
ACL