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        <title>The E2E Dataset: New Challenges For End-to-End Generation</title>
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            <namePart type="given">Kristiina</namePart>
            <namePart type="family">Jokinen</namePart>
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            <namePart type="given">Manfred</namePart>
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    <abstract>This paper describes the E2E data, a new dataset for training end-to-end, data-driven natural language generation systems in the restaurant domain, which is ten times bigger than existing, frequently used datasets in this area. The E2E dataset poses new challenges: (1) its human reference texts show more lexical richness and syntactic variation, including discourse phenomena; (2) generating from this set requires content selection. As such, learning from this dataset promises more natural, varied and less template-like system utterances. We also establish a baseline on this dataset, which illustrates some of the difficulties associated with this data.</abstract>
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%0 Conference Proceedings
%T The E2E Dataset: New Challenges For End-to-End Generation
%A Novikova, Jekaterina
%A Dušek, Ondřej
%A Rieser, Verena
%Y Jokinen, Kristiina
%Y Stede, Manfred
%Y DeVault, David
%Y Louis, Annie
%S Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue
%D 2017
%8 August
%I Association for Computational Linguistics
%C Saarbrücken, Germany
%F novikova-etal-2017-e2e
%X This paper describes the E2E data, a new dataset for training end-to-end, data-driven natural language generation systems in the restaurant domain, which is ten times bigger than existing, frequently used datasets in this area. The E2E dataset poses new challenges: (1) its human reference texts show more lexical richness and syntactic variation, including discourse phenomena; (2) generating from this set requires content selection. As such, learning from this dataset promises more natural, varied and less template-like system utterances. We also establish a baseline on this dataset, which illustrates some of the difficulties associated with this data.
%R 10.18653/v1/W17-5525
%U https://aclanthology.org/W17-5525
%U https://doi.org/10.18653/v1/W17-5525
%P 201-206

Markdown (Informal)

[The E2E Dataset: New Challenges For End-to-End Generation](https://aclanthology.org/W17-5525) (Novikova et al., SIGDIAL 2017)

• The E2E Dataset: New Challenges For End-to-End Generation (Novikova et al., SIGDIAL 2017)

ACL

• Jekaterina Novikova, Ondřej Dušek, and Verena Rieser. 2017. The E2E Dataset: New Challenges For End-to-End Generation. In Proceedings of the 18th Annual SIGdial Meeting on Discourse and Dialogue, pages 201–206, Saarbrücken, Germany. Association for Computational Linguistics.