How can we measure the relevancy of responses with regard to user utterances in human robot interaction?

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Mohamed-Mourad Lafifi

Dear Tahir,

I suggest you to see links and attached files on topic.

-Evaluating the Engagement with Social Robots - HAL-Inria

https://hal.inria.fr/hal-01158293/document

-40-Affect in Human-Robot Interaction - Semantic Scholar

https://pdfs.semanticscholar.org/.../f7b4f48e4aa6b9d1c1748b746e...

-Estimating response obligation in multi-party human-robot dialogues ...

https://www.researchgate.net/.../308658965_Estimating_response_...

-Measuring Habituation during Human-Robot Interaction - SOCRATES

www.socrates-project.eu/internal.../SSR.../SSR_2018_paper_19.pd...

-Affect in Human-Robot Interaction - Georgia Tech College of Computing

www.cc.gatech.edu/ai/robot-lab/online-publications/Affect-Article.ps.gz

Best regards

Tahir Abbas

Mohamed-Mourad Lafifi Thank you for this. I saw some broken links. Can you check that please?

Hi Tahir,

For broken links you can use title's link only and it should work normally.

Maximilian Metzner

An established approach today is the detection of special keywords or phrases to signal relevancy (see classic home automation, e.g. Alexa, Google Home). All other utterances are simply ignored. AI can greatly help recognize these keywords in real-life scenarios with background noise etc. It can also be used to differentiate between different users (with potentially different permissions with regard to robot interaction).

Another approach is the fusion of different sensor data (e.g. Motion Capturing, Eye Tracking) to evaluate who the human is talking to. Simply put, if the human is looking at or is turned towards the robot, he wants to actively interact.

See for example Conference Paper Human-Robot-Interaction for mobile industrial robot teams