FIAT/IFTA World Conference 2024

Despite considerable research on explicitly sexualized talk as a form of gender micro-aggression, hostility and harassment, it is still unclear how does talking about less-explicitly sexualizing but no less gendered issue such as beauty, shape the paralinguistics of interaction. Taking the topic of human beauty as our case study and utilizing short moments from TV and film archives, we therefore ask:

1) How does talking about an explicitly gendered issue (beauty) contribute to the overall gendering of audiovisual cultural objects?

2) How do the paralinguistic aspects of audiovisual gendered interactions shift overtime?

This proof of concept (POC) research is testing the usefulness of experimental AI methods to reveal the multilayered effect of gender on interactions. The POC consists of two one-on-one interviews in which beauty is a specifically mentioned topic, with two women beauty queens. The two samples represent two periods of “beauty talk” – one from the 1970ies and one from the 2010s.

Following the design of a set of coding labels, we will index two videos manually and then compare the qualitative process to an automatic indexing of these videos using an AI indexing tool. Among its analytical insights, we will automatically extract multimodal information and insights such as automatic transcription of spoken Hebrew; Speaker identification, vocal effects (such as laughter or long silences), sentiment analysis, and more.

The comparison will help identify specific spoken/visual/vocal profiles of both interviewers and interviewees, as well as of the interactions between them and to set the Beauty features that would be included in the training of a future study, on a large scale database of interviews. Using both human and AI labeling, this POC research hopes to contribute to a more precise hermeneutic interpretations of the human beauty concept and to enable a “distant reading, viewing, and listening” of these multimodal artifacts.