Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations

Marco Antonio Sobrevilla Cabezudo; Simon Mille; Thiago Alexandre Salgueiro Pardo

Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations

Marco Antonio Sobrevilla Cabezudo, Simon Mille, Thiago Alexandre Salgueiro Pardo

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

8 Citas (Scopus)

Resumen

This paper presents an exploratory study that aims to evaluate the usefulness of back-translation in Natural Language Generation (NLG) from semantic representations for non-English languages. Specifically, Abstract Meaning Representation and Brazilian Portuguese (BP) are chosen as semantic representation and language, respectively. Two methods (focused on Statistical and Neural Machine Translation) are evaluated on two datasets (one automatically generated and another one human-generated) to compare the performance in a real context. Also, several cuts according to quality measures are performed to evaluate the importance (or not) of the data quality in NLG. Results show that there are still many improvements to be made but this is a promising approach.

Idioma original	Inglés
Título de la publicación alojada	MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings
Editorial	Association for Computational Linguistics (ACL)
Páginas	94-103
Número de páginas	10
ISBN (versión digital)	9781950737765
Estado	Publicada - 2019
Publicado de forma externa	Sí
Evento	2nd Workshop on Multilingual Surface Realisation, MSR@EMNLP-IJCNLP 2019 - Hong Kong, China Duración: 3 nov. 2019 → …

Serie de la publicación

Nombre	MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings

Conferencia

Conferencia	2nd Workshop on Multilingual Surface Realisation, MSR@EMNLP-IJCNLP 2019
País/Territorio	China
Ciudad	Hong Kong
Período	3/11/19 → …

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Cabezudo, M. A. S., Mille, S., & Pardo, T. A. S. (2019). Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations. En MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings (pp. 94-103). (MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings). Association for Computational Linguistics (ACL).

Cabezudo, Marco Antonio Sobrevilla ; Mille, Simon ; Pardo, Thiago Alexandre Salgueiro. / Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations. MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings. Association for Computational Linguistics (ACL), 2019. pp. 94-103 (MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings).

@inproceedings{a9e34663f3f14cd9a3fe65b291758a5b,

title = "Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations",

abstract = "This paper presents an exploratory study that aims to evaluate the usefulness of back-translation in Natural Language Generation (NLG) from semantic representations for non-English languages. Specifically, Abstract Meaning Representation and Brazilian Portuguese (BP) are chosen as semantic representation and language, respectively. Two methods (focused on Statistical and Neural Machine Translation) are evaluated on two datasets (one automatically generated and another one human-generated) to compare the performance in a real context. Also, several cuts according to quality measures are performed to evaluate the importance (or not) of the data quality in NLG. Results show that there are still many improvements to be made but this is a promising approach.",

author = "Cabezudo, {Marco Antonio Sobrevilla} and Simon Mille and Pardo, {Thiago Alexandre Salgueiro}",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computational Linguistics.; 2nd Workshop on Multilingual Surface Realisation, MSR@EMNLP-IJCNLP 2019 ; Conference date: 03-11-2019",

year = "2019",

language = "English",

series = "MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings",

publisher = "Association for Computational Linguistics (ACL)",

pages = "94--103",

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Cabezudo, MAS, Mille, S & Pardo, TAS 2019, Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations. En MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings. MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings, Association for Computational Linguistics (ACL), pp. 94-103, 2nd Workshop on Multilingual Surface Realisation, MSR@EMNLP-IJCNLP 2019, Hong Kong, China, 3/11/19.

Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations. / Cabezudo, Marco Antonio Sobrevilla; Mille, Simon; Pardo, Thiago Alexandre Salgueiro.
MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings. Association for Computational Linguistics (ACL), 2019. p. 94-103 (MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings).

Producción científica: Capítulo del libro/informe/acta de congreso › Contribución a la conferencia › revisión exhaustiva

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T1 - Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations

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Y1 - 2019

N2 - This paper presents an exploratory study that aims to evaluate the usefulness of back-translation in Natural Language Generation (NLG) from semantic representations for non-English languages. Specifically, Abstract Meaning Representation and Brazilian Portuguese (BP) are chosen as semantic representation and language, respectively. Two methods (focused on Statistical and Neural Machine Translation) are evaluated on two datasets (one automatically generated and another one human-generated) to compare the performance in a real context. Also, several cuts according to quality measures are performed to evaluate the importance (or not) of the data quality in NLG. Results show that there are still many improvements to be made but this is a promising approach.

AB - This paper presents an exploratory study that aims to evaluate the usefulness of back-translation in Natural Language Generation (NLG) from semantic representations for non-English languages. Specifically, Abstract Meaning Representation and Brazilian Portuguese (BP) are chosen as semantic representation and language, respectively. Two methods (focused on Statistical and Neural Machine Translation) are evaluated on two datasets (one automatically generated and another one human-generated) to compare the performance in a real context. Also, several cuts according to quality measures are performed to evaluate the importance (or not) of the data quality in NLG. Results show that there are still many improvements to be made but this is a promising approach.

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M3 - Conference contribution

AN - SCOPUS:85097971963

T3 - MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings

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BT - MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings

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Cabezudo MAS, Mille S, Pardo TAS. Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations. En MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings. Association for Computational Linguistics (ACL). 2019. p. 94-103. (MSR@EMNLP-IJCNLP 2019 - 2nd Workshop on Multilingual Surface Realisation, Proceedings).

Back-translation as strategy to tackle the lack of corpus in natural language generation from semantic representations

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