Automatically detecting personality traits can aid several applications, such as mental health recognition and human resource management. Most datasets introduced for personality detection so far have analyzed these traits for each individual in isolation. However, personality is intimately linked to our social behavior. Furthermore, surprisingly little research has focused on personality analysis using low resource languages. To this end, we present a novel peer-to-peer Hindi conversation dataset- Vyaktitv. It consists of high-quality audio and video recordings of the participants, with Hinglish textual transcriptions for each conversation. The dataset also contains a rich set of socio-demographic features, like income, cultural orientation, amongst several others, for all the participants. We release the dataset for public use, as well as perform preliminary statistical analysis along the different dimensions. Finally, we also discuss various other applications and tasks for which the dataset can be employed.

中文翻译：

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Vyaktitv：基于多模态点对点印地语对话的个性评估数据集

自动检测个性特征可以帮助多种应用，例如心理健康识别和人力资源管理。迄今为止，大多数用于个性检测的数据集都单独分析了每个人的这些特征。然而，个性与我们的社会行为密切相关。此外，令人惊讶的是，很少有研究关注使用低资源语言的个性分析。为此，我们提出了一个新颖的点对点印地语对话数据集——Vyaktitv。它由参与者的高质量音频和视频记录组成，每个对话都有 Hinglish 文本转录。该数据集还包含一组丰富的社会人口特征，如收入、文化取向等，适用于所有参与者。我们发布数据集供公众使用，以及沿不同维度进行初步统计分析。最后，我们还讨论了可以使用数据集的各种其他应用程序和任务。