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LREC-COLING 2024main

CAMERA³: An Evaluation Dataset for Controllable Ad Text Generation in Japanese

Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

DOI:10.63317/2vhxpg3vbyrc

Abstract

Ad text generation is the task of creating compelling text from an advertising asset that describes products or services, such as a landing page. In advertising, diversity plays an important role in enhancing the effectiveness of an ad text, mitigating a phenomenon called “ad fatigue,” where users become disengaged due to repetitive exposure to the same advertisement. Despite numerous efforts in ad text generation, the aspect of diversifying ad texts has received limited attention, particularly in non-English languages like Japanese. To address this, we present CAMERA³, an evaluation dataset for controllable text generation in the advertising domain in Japanese. Our dataset includes 3,980 ad texts written by expert annotators, taking into account various aspects of ad appeals. We make CAMERA³ publicly available, allowing researchers to examine the capabilities of recent NLG models in controllable text generation in a real-world scenario.

Details

Paper ID
lrec2024-main-0242
Pages
pp. 2702-2707
BibKey
inoue-etal-2024-camera3
Editor
N/A
Publisher
European Language Resources Association (ELRA) and ICCL
ISSN
2522-2686
ISBN
979-10-95546-34-4
Conference
Joint International Conference on Computational Linguistics, Language Resources and Evaluation
Location
Turin, Italy
Date
20 May 2024 25 May 2024

Authors

  • GI

    Go Inoue

  • AK

    Akihiko Kato

  • MM

    Masato Mita

  • UH

    Ukyo Honda

  • PZ

    Peinan Zhang

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