Detecting Driver Frustration from Audio and Video in the Wild

This blog post accompanies a paper we presented at the 2016 International Joint Conference on Artificial Intelligence (IJCAI) in New York City. You can download the paper here. Let’s start with a motivating question:

Question: Which one of these 2 drivers appears frustrated?


The answer is counterintuitive, especially from the generic affective computing perspective that would be much more likely to see the driver on the left as the more frustrated one. In fact, on a scale of 1 to 10 (where 1 is least frustrated and 10 is most frustrated), the driver on the left self-reported a frustration level of 1, while the driver on the right self-reported a frustration level of 9. Watch the following video to understand how “frustration” in the context of driving and using a voice-based navigation system may be different than the more generic affective concept of “frustration.”


Irman Abdić, TUM, MIT
Lex Fridman, MIT (contact author:
Daniel McDuff, MIT
Erik Marchi, TUM
Bryan Reimer, MIT
Björn W. Schuller, Imperial College London, University of Passau