Giving Robots a Voice: Human-in-the-Loop Voice Creation and open-ended Labeling

Fuente: arXiv
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Main Authors: van Rijn, Pol, Mertes, Silvan, Janowski, Kathrin, Weitz, Katharina, Jacoby, Nori, André, Elisabeth
Format: Preprint
Published: 2024
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author van Rijn, Pol
Mertes, Silvan
Janowski, Kathrin
Weitz, Katharina
Jacoby, Nori
André, Elisabeth
author_facet van Rijn, Pol
Mertes, Silvan
Janowski, Kathrin
Weitz, Katharina
Jacoby, Nori
André, Elisabeth
contents Speech is a natural interface for humans to interact with robots. Yet, aligning a robot's voice to its appearance is challenging due to the rich vocabulary of both modalities. Previous research has explored a few labels to describe robots and tested them on a limited number of robots and existing voices. Here, we develop a robot-voice creation tool followed by large-scale behavioral human experiments (N=2,505). First, participants collectively tune robotic voices to match 175 robot images using an adaptive human-in-the-loop pipeline. Then, participants describe their impression of the robot or their matched voice using another human-in-the-loop paradigm for open-ended labeling. The elicited taxonomy is then used to rate robot attributes and to predict the best voice for an unseen robot. We offer a web interface to aid engineers in customizing robot voices, demonstrating the synergy between cognitive science and machine learning for engineering tools.
format Preprint
id arxiv_https___arxiv_org_abs_2402_05206
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Giving Robots a Voice: Human-in-the-Loop Voice Creation and open-ended Labeling
van Rijn, Pol
Mertes, Silvan
Janowski, Kathrin
Weitz, Katharina
Jacoby, Nori
André, Elisabeth
Human-Computer Interaction
Robotics
Speech is a natural interface for humans to interact with robots. Yet, aligning a robot's voice to its appearance is challenging due to the rich vocabulary of both modalities. Previous research has explored a few labels to describe robots and tested them on a limited number of robots and existing voices. Here, we develop a robot-voice creation tool followed by large-scale behavioral human experiments (N=2,505). First, participants collectively tune robotic voices to match 175 robot images using an adaptive human-in-the-loop pipeline. Then, participants describe their impression of the robot or their matched voice using another human-in-the-loop paradigm for open-ended labeling. The elicited taxonomy is then used to rate robot attributes and to predict the best voice for an unseen robot. We offer a web interface to aid engineers in customizing robot voices, demonstrating the synergy between cognitive science and machine learning for engineering tools.
title Giving Robots a Voice: Human-in-the-Loop Voice Creation and open-ended Labeling
topic Human-Computer Interaction
Robotics
url https://arxiv.org/abs/2402.05206