# ManzaiSet: A Multimodal Dataset of Viewer Responses to Japanese Manzai Comedy

arXiv: https://arxiv.org/abs/2510.18014 · HTML: https://mlsanity.com/paper/2510.18014/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 7 of its 27 references that are in the map.
- First posted on arXiv 20 Oct 2025.

## Builds on (most cited first, 7 of 7)

- [Robust Speech Recognition via Large-Scale Weak Supervision](https://mlsanity.com/paper/2212.04356/) (2022)
- [AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild](https://mlsanity.com/paper/1708.03985/) (2017)
- [Expression, Affect, Action Unit Recognition: Aff-Wild2, Multi-Task Learning and ArcFace](https://mlsanity.com/paper/1910.04855/) (2019)
- [UR-FUNNY: A Multimodal Language Dataset for Understanding Humor](https://mlsanity.com/paper/1904.06618/) (2019)
- [SEWA DB: A Rich Database for Audio-Visual Emotion and Sentiment Research in the Wild](https://mlsanity.com/paper/1901.02839/) (2019)
- [SMILE: Multimodal Dataset for Understanding Laughter in Video with Language Models](https://mlsanity.com/paper/2312.09818/) (2023)
- [StandUp4AI: A New Multilingual Dataset for Humor Detection in Stand-up Comedy Videos](https://mlsanity.com/paper/2505.18903/) (2025)

## Abstract (arXiv)

We introduce ManzaiSet, a multimodal dataset of individual viewer responses to Japanese manzai comedy. The corpus contains 2,301 viewer-performance recordings from 241 native Japanese speakers, totaling 191.8 hours of facial video and microphone audio. Participants watched up to 10 shared professional performances in randomized order at home and rated each performance on a 0-100 scale. Exploratory analyses yielded three findings. First, viewers differed in both their average ratings and how much their ratings varied across performances. Viewers who rated one random half of the performances highly also tended to rate the other half highly within the same viewing sequence. Second, performances watched later in the sequence received higher ratings on average. Third, after multiple-comparison correction, no statistically significant differences in viewer responses were found between humor categories. ManzaiSet supports the study of individual differences by linking shared Japanese comedy performances to viewer ratings, viewing order, and audiovisual responses.