Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach

Benyamin Ahmadnia; Gholamreza Haffari; Javier Serrano

doi:10.1109/CIST.2018.8596614

Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach

Benyamin Ahmadnia, Gholamreza Haffari, Javier Serrano

Department of Data Science & AI

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

5 Citations (Scopus)

Abstract

In this paper we apply the round-tripping algorithm to Statistical Machine Translation (SMT) for making effective use of monolingual data to tackle the training data scarcity. In this approach, the outbound-trip (forward) and inbound-trip (backward) translation tasks make a closed loop, and produce informative feedback to train the translation models. Based on this produced feedback we iteratively update the forward and backward translation models. The experimental results show that translation quality is improved for Persian\leftrightarrow Spanish translation task.

Original language	English
Title of host publication	5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18
Subtitle of host publication	Marrakech, Morocco, October 21-27, 2018
Editors	Ismaii Jeiiouii
Place of Publication	Piscataway NJ USA
Publisher	IEEE, Institute of Electrical and Electronics Engineers
Pages	261-265
Number of pages	5
ISBN (Electronic)	9781538643853
ISBN (Print)	9781538643860
DOIs	https://doi.org/10.1109/CIST.2018.8596614
Publication status	Published - 2018
Event	International Congress on Information Science and Technology 2018 - Marrakech, Morocco Duration: 21 Oct 2018 → 27 Oct 2018 Conference number: 5th http://www.ieee.ma/cist18/

Publication series

Name	Colloquium in Information Science and Technology, CIST
Volume	2018-October
ISSN (Print)	2327-185X
ISSN (Electronic)	2327-1884

Conference

Conference	International Congress on Information Science and Technology 2018
Abbreviated title	CiSt 2018
Country/Territory	Morocco
City	Marrakech
Period	21/10/18 → 27/10/18
Internet address	http://www.ieee.ma/cist18/

Keywords

low-resource languages
natural language processing
round-tripping algorithm
statistical machine translation

Access to Document

10.1109/CIST.2018.8596614

Cite this

Ahmadnia, B., Haffari, G., & Serrano, J. (2018). Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach. In I. Jeiiouii (Ed.), 5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18: Marrakech, Morocco, October 21-27, 2018 (pp. 261-265). (Colloquium in Information Science and Technology, CIST; Vol. 2018-October). IEEE, Institute of Electrical and Electronics Engineers. https://doi.org/10.1109/CIST.2018.8596614

Ahmadnia, Benyamin ; Haffari, Gholamreza ; Serrano, Javier. / Statistical Machine Translation for bilingually low-resource scenarios : a round-tripping approach. 5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18: Marrakech, Morocco, October 21-27, 2018. editor / Ismaii Jeiiouii. Piscataway NJ USA : IEEE, Institute of Electrical and Electronics Engineers, 2018. pp. 261-265 (Colloquium in Information Science and Technology, CIST).

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abstract = "In this paper we apply the round-tripping algorithm to Statistical Machine Translation (SMT) for making effective use of monolingual data to tackle the training data scarcity. In this approach, the outbound-trip (forward) and inbound-trip (backward) translation tasks make a closed loop, and produce informative feedback to train the translation models. Based on this produced feedback we iteratively update the forward and backward translation models. The experimental results show that translation quality is improved for Persian\leftrightarrow Spanish translation task.",

keywords = "low-resource languages, natural language processing, round-tripping algorithm, statistical machine translation",

author = "Benyamin Ahmadnia and Gholamreza Haffari and Javier Serrano",

year = "2018",

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editor = "Ismaii Jeiiouii",

booktitle = "5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18",

address = "United States of America",

note = "International Congress on Information Science and Technology 2018, CiSt 2018 ; Conference date: 21-10-2018 Through 27-10-2018",

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Ahmadnia, B, Haffari, G & Serrano, J 2018, Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach. in I Jeiiouii (ed.), 5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18: Marrakech, Morocco, October 21-27, 2018. Colloquium in Information Science and Technology, CIST, vol. 2018-October, IEEE, Institute of Electrical and Electronics Engineers, Piscataway NJ USA, pp. 261-265, International Congress on Information Science and Technology 2018, Marrakech, Morocco, 21/10/18. https://doi.org/10.1109/CIST.2018.8596614

Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach. / Ahmadnia, Benyamin; Haffari, Gholamreza; Serrano, Javier.
5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18: Marrakech, Morocco, October 21-27, 2018. ed. / Ismaii Jeiiouii. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, 2018. p. 261-265 (Colloquium in Information Science and Technology, CIST; Vol. 2018-October).

Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research

TY - GEN

T1 - Statistical Machine Translation for bilingually low-resource scenarios

T2 - International Congress on Information Science and Technology 2018

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AU - Haffari, Gholamreza

AU - Serrano, Javier

N1 - Conference code: 5th

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N2 - In this paper we apply the round-tripping algorithm to Statistical Machine Translation (SMT) for making effective use of monolingual data to tackle the training data scarcity. In this approach, the outbound-trip (forward) and inbound-trip (backward) translation tasks make a closed loop, and produce informative feedback to train the translation models. Based on this produced feedback we iteratively update the forward and backward translation models. The experimental results show that translation quality is improved for Persian\leftrightarrow Spanish translation task.

AB - In this paper we apply the round-tripping algorithm to Statistical Machine Translation (SMT) for making effective use of monolingual data to tackle the training data scarcity. In this approach, the outbound-trip (forward) and inbound-trip (backward) translation tasks make a closed loop, and produce informative feedback to train the translation models. Based on this produced feedback we iteratively update the forward and backward translation models. The experimental results show that translation quality is improved for Persian\leftrightarrow Spanish translation task.

KW - low-resource languages

KW - natural language processing

KW - round-tripping algorithm

KW - statistical machine translation

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U2 - 10.1109/CIST.2018.8596614

DO - 10.1109/CIST.2018.8596614

M3 - Conference Paper

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T3 - Colloquium in Information Science and Technology, CIST

SP - 261

EP - 265

BT - 5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18

A2 - Jeiiouii, Ismaii

PB - IEEE, Institute of Electrical and Electronics Engineers

CY - Piscataway NJ USA

Y2 - 21 October 2018 through 27 October 2018

ER -

Ahmadnia B, Haffari G, Serrano J. Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach. In Jeiiouii I, editor, 5th International IEEE Congress on Information Science and Technology, IEEE CiSt'18: Marrakech, Morocco, October 21-27, 2018. Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers. 2018. p. 261-265. (Colloquium in Information Science and Technology, CIST). doi: 10.1109/CIST.2018.8596614

Statistical Machine Translation for bilingually low-resource scenarios: a round-tripping approach

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