Document Type
Conference Proceeding
Publication Date
2018
Abstract
When interacting with robots in a situated spoken dialogue setting, human dialogue partners tend to assign anthropomorphic and social characteristics to those robots. In this paper, we explore the age and educational level that human dialogue partners assign to three different robotic systems, including an un-embodied spoken dialogue system. We found that how a robot speaks is as important to human perceptions as the way the robot looks. Using the data from our experiment, we derived prosodic, emotional, and linguistic features from the participants to train and evaluate a classifier that predicts perceived intelligence, age, and education level.
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Publication Information
Plane, Sarah; Marvasti, Ariel; Egan, Tyler; and Kennington, Casey. (2018). "Predicting Perceived Age: Both Language Ability and Appearance are Important". Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, 130-139. https://doi.org/10.18653/v1/W18-5014