论文标题
vyaktitv：基于个性评估的基于多模式的点对点印地语对话数据集
Vyaktitv: A Multimodal Peer-to-Peer Hindi Conversations based Dataset for Personality Assessment
论文作者
论文摘要
自动检测性格特征可以帮助多种应用，例如心理健康认识和人力资源管理。到目前为止，大多数用于人格检测的数据集都孤立地分析了每个人的这些特征。但是，个性与我们的社会行为密切相关。此外，令人惊讶的是，很少有研究重点是使用低资源语言进行人格分析。为此，我们提出了一个新颖的对等印地语对话数据集-Vyaktitv。它由参与者的高质量音频和视频录制组成，每次对话都有文字转录。该数据集还包含一系列社会人口统计学特征，例如收入，文化取向等其他参与者。我们发布数据集供公众使用，并沿不同维度执行初步统计分析。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。
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.
