# Vyaktitv: A Multimodal Peer-to-Peer Hindi Conversations based Dataset for Personality Assessment

arXiv: https://arxiv.org/abs/2008.13769 · HTML: https://mlsanity.com/paper/2008.13769/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 31 Aug 2020.

## Built on by (most cited first, 4 of 4)

- [Didn't see that coming: a survey on non-verbal social human behavior forecasting](https://mlsanity.com/paper/2203.02480/) (2022)
- [Exploring Semi-Supervised Learning for Predicting Listener Backchannels](https://mlsanity.com/paper/2101.01899/) (2021)
- [Co-Located Human-Human Interaction Analysis using Nonverbal Cues: A Survey](https://mlsanity.com/paper/2207.10574/) (2022)
- [Inferred vs traditional personality assessment: are we predicting the same thing?](https://mlsanity.com/paper/2103.09632/) (2021)

## Abstract (arXiv)

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.