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Published March 7, 2023 | Version v1
Dataset Restricted

Multimodal Defensive Communication Database (DefComm-DB)

Authors/Creators

  • 1. Anonymised for review

Contributors

Contact person:

Data collector:

  • 1. Anonymised for review

Description

Description: DefComm-DB comprises 261 genuine non-acted dialogues between English-speaking individuals in 'real-world' settings that feature one of the defensive behaviours outlined in Birkenbihl's model of communication failures [1]:

  1. Attacking the conversation partner (class Attack): videos that depict individuals actively attacking verbally, blaming the other person, or shifting the other person's attention to themselves.
  2. Withdrawing from the communication (class Flight): videos where people refuse to respond, withdraw from the conversation or change the topic or focus.
  3. Making oneself greater (class Greater): videos that depict individuals boasting, self-justifying in an aggressive manner, denying accusations, exhibiting a sense of dominance or superiority, or expressing indignation.
  4. Making oneself smaller (class Smaller): videos that display individuals engaging in self-deprecation, self-blame, exhibiting a sense of guilt, apologising, and expressing feelings of vulnerability or worthlessness.

[1] Birkenbihl, V. (2013). Kommunikationstraining: Zwischenmenschliche Beziehungen erfolgreich gestalten. Schritte 1–6. : mvg Verlag.

Key statistics on the dataset are provided in Table 1. DefComm features a variety of video topics, including interviews with celebrities and professional athletes, political debates, legal trials, TV shows, and video footage obtained by paparazzi, among others. The situations, number of participants, gender, age, and ethnicity vary from scene to scene.

From each video, we retrieve audio, visual, and textual modalities. In this paper, we focus on the audio modality and the speech transcriptions.

Table 1: Statistics on Def-Comm: number of video clips, mean duration (μ), standard deviation (σ), minimum, maximum, and total duration of collected videos per class.
Label # video clips μ [s] σ [s] min [s] max [s] Σ duration [s]
Attack 112 8 9 2 46 949
Flight 57 9 8 2 62 494
Greater 45 9 6 2 25 416
Smaller 47 12 8 3 49 556
Total 261 9 8 2 62 2415

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Conditions

This dataset can be shared with academic researchers for non-commercial research purposes only.

1. Intended use

The dataset can only be used for the purpose of benchmarking multimodal defensive communication classification or affective systems.

2. Responsibility

The data requester must hold a permanent position at an academic institute. Up to five other researchers affiliated with the same institute may be named (e.g. PhD students), which will allow them to work with this dataset. We are not responsible for the content or the meaning of the videos.

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