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        <title>Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek</title>
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    <name type="personal">
        <namePart type="given">Alejandro</namePart>
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    <name type="personal">
        <namePart type="given">Álvaro</namePart>
        <namePart type="family">Barbero Jiménez</namePart>
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            <title>Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022</title>
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            <namePart type="given">Mahmoud</namePart>
            <namePart type="family">El-Haj</namePart>
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            <namePart type="given">Paul</namePart>
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    <abstract>This paper describes the three summarization systems submitted to the Financial Narrative Summarization Shared Task (FNS-2022). We developed a task-specific extractive summarization method for the reports in English. It was based on a sequence classification task whose objective was to find the sentence where the summary begins. On the other hand, since the summaries for the reports in Spanish and Greek were not extractive, we used an abstractive strategy for each of the languages. In particular, we created a new Encoder-Decoder architecture in Spanish, MariMari, based on an existing Encoding-only model; we also trained multilingual Encoder-Decoder models for this task. Finally, the summaries for the reports in Greek were obtained with a translation-summary-translation system in which the reports were translated to English and summarised, and then the summaries were translated back to Greek.</abstract>
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        <date>2022-06</date>
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%0 Conference Proceedings
%T Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek
%A Vaca, Alejandro
%A Segurado, Alba
%A Betancur, David
%A Barbero Jiménez, Álvaro
%Y El-Haj, Mahmoud
%Y Rayson, Paul
%Y Zmandar, Nadhem
%S Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022
%D 2022
%8 June
%I European Language Resources Association
%C Marseille, France
%F vaca-etal-2022-extractive
%X This paper describes the three summarization systems submitted to the Financial Narrative Summarization Shared Task (FNS-2022). We developed a task-specific extractive summarization method for the reports in English. It was based on a sequence classification task whose objective was to find the sentence where the summary begins. On the other hand, since the summaries for the reports in Spanish and Greek were not extractive, we used an abstractive strategy for each of the languages. In particular, we created a new Encoder-Decoder architecture in Spanish, MariMari, based on an existing Encoding-only model; we also trained multilingual Encoder-Decoder models for this task. Finally, the summaries for the reports in Greek were obtained with a translation-summary-translation system in which the reports were translated to English and summarised, and then the summaries were translated back to Greek.
%U https://aclanthology.org/2022.fnp-1.8
%P 59-64

Markdown (Informal)

[Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek](https://aclanthology.org/2022.fnp-1.8) (Vaca et al., FNP 2022)

• Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek (Vaca et al., FNP 2022)

ACL

• Alejandro Vaca, Alba Segurado, David Betancur, and Álvaro Barbero Jiménez. 2022. Extractive and Abstractive Summarization Methods for Financial Narrative Summarization in English, Spanish and Greek. In Proceedings of the 4th Financial Narrative Processing Workshop @LREC2022, pages 59–64, Marseille, France. European Language Resources Association.