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        <title>Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls</title>
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    <abstract>In various scenarios, such as conference oral presentations, company managers’ talks, and politicians’ speeches, individuals often contemplate the potential questions that may arise from their presentations. This common practice prompts the research question addressed in this study: to what extent can models generate multiple questions based on a given presentation transcript? To investigate this, we conduct pilot explorations using earnings conference call transcripts, which serve as regular meetings between professional investors and company managers. We experiment with different task settings and methods and evaluate the results from various perspectives. Our findings highlight that incorporating key points retrieval techniques enhances the accuracy and diversity of the generated questions.</abstract>
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%0 Conference Proceedings
%T Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls
%A Juan, Yining
%A Chen, Chung-Chi
%A Huang, Hen-Hsen
%A Chen, Hsin-Hsi
%Y Keet, C. Maria
%Y Lee, Hung-Yi
%Y Zarrieß, Sina
%S Proceedings of the 16th International Natural Language Generation Conference
%D 2023
%8 September
%I Association for Computational Linguistics
%C Prague, Czechia
%F juan-etal-2023-generating
%X In various scenarios, such as conference oral presentations, company managers’ talks, and politicians’ speeches, individuals often contemplate the potential questions that may arise from their presentations. This common practice prompts the research question addressed in this study: to what extent can models generate multiple questions based on a given presentation transcript? To investigate this, we conduct pilot explorations using earnings conference call transcripts, which serve as regular meetings between professional investors and company managers. We experiment with different task settings and methods and evaluate the results from various perspectives. Our findings highlight that incorporating key points retrieval techniques enhances the accuracy and diversity of the generated questions.
%R 10.18653/v1/2023.inlg-main.35
%U https://aclanthology.org/2023.inlg-main.35
%U https://doi.org/10.18653/v1/2023.inlg-main.35
%P 449-454

Markdown (Informal)

[Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls](https://aclanthology.org/2023.inlg-main.35) (Juan et al., INLG-SIGDIAL 2023)

• Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls (Juan et al., INLG-SIGDIAL 2023)

ACL

• Yining Juan, Chung-Chi Chen, Hen-Hsen Huang, and Hsin-Hsi Chen. 2023. Generating Multiple Questions from Presentation Transcripts: A Pilot Study on Earnings Conference Calls. In Proceedings of the 16th International Natural Language Generation Conference, pages 449–454, Prague, Czechia. Association for Computational Linguistics.