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This does not allow to investigate how people\u2019s judgements develop over time during presentations. This contrasts with primacy and recency theories, which suggest that some moments of the speech could be more salient than others and contribute disproportionately to the perception of the speaker\u2019s performance. To provide novel insights on this phenomenon, we present the 3MT_French dataset. It contains a set of public speaking annotations collected on a crowd-sourcing platform through a novel annotation scheme and protocol. Global evaluation, persuasiveness, perceived self-confidence of the speaker and audience engagement were annotated on different time windows (i.e., the beginning, middle or end of the presentation, or the full video). This new resource will be useful to researchers working on public speaking assessment and training. It will allow to fine-tune the analysis of presentations under a novel perspective relying on socio-cognitive theories rarely studied before in this context, such as first impressions and primacy and recency theories. An exploratory correlation analysis on the annotations provided in the dataset suggests that the early moments of a presentation have a stronger impact on the judgements.<\/jats:p>","DOI":"10.1007\/s10579-023-09709-5","type":"journal-article","created":{"date-parts":[[2024,3,23]],"date-time":"2024-03-23T03:10:03Z","timestamp":1711163403000},"page":"371-390","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Introducing the 3MT_French dataset to investigate the timing of public speaking judgements"],"prefix":"10.1007","volume":"59","author":[{"given":"Beatrice","family":"Biancardi","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Mathieu","family":"Chollet","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Chlo\u00e9","family":"Clavel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2024,3,23]]},"reference":[{"issue":"2","key":"9709_CR1","doi-asserted-by":"publisher","first-page":"256","DOI":"10.1037\/0033-2909.111.2.256","volume":"111","author":"N Ambady","year":"1992","unstructured":"Ambady, N., & Rosenthal, R. 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One potential ethical concern related to the dataset would be to use the data to automatically judge the quality of a speech. This is not the purpose of our work, since we are interested in understanding how people form their judgements and to develop training tools to improve public speaking skills. As in all research activities involving human beings, gender differences may exist. Potential gender bias need to be addressed by the researchers interested in using the 3MT_French dataset as an integral part of their analyses to ensure the highest level of scientific quality. The gender of the speaker is provided, while no information about the gender of the annotators was collected through the Amazon Mechanical Turk platform.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethical approval"}}]}}