A Review of Personality in Voice-Based Man Machine Interaction

Metze, Florian; Black, Alan W.; Polzehl, Tim

doi:10.1007/978-3-642-21605-3_40

Cited by 6 publications

(3 citation statements)

References 17 publications

(21 reference statements)

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“…As evaluation measure, we stick with unweighted average (UA) recall as used since the first Challenge held in 2009 [10]. In the 1 : arithmetic mean of LLD / positive ∆ LLD. 2 : only applied to voice related LLD.…”

Section: Challenge Baselinesmentioning

confidence: 99%

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The INTERSPEECH 2012 speaker trait challenge

et al. 2012

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The INTERSPEECH 2012 Speaker Trait Challenge provides for the first time a unified test-bed for 'perceived' speaker traits: Personality in the five OCEAN personality dimensions, likability of speakers, and intelligibility of pathologic speakers. In this paper, we describe these three Sub-Challenges, Challenge conditions, baselines, and a new feature set by the openSMILE toolkit, provided to the participants.

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Section: Challenge Baselinesmentioning

confidence: 99%

“…By that -as opposed to the INTERSPEECH 2010 Paralinguistic Challenge -we now deal with perceived speaker traits. Apart from intelligent and socially competent future agents and robots [1], main applications are found in the medical domain and surveillance.…”

Section: Introductionmentioning

confidence: 99%

The INTERSPEECH 2012 speaker trait challenge

et al. 2012

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“…The first experiment presented a comparison between the cheerful and the serious personalities, which were reflected in the robots’ voices ( Nass and Lee, 2000 ) by asserting the same speed and different voice shaping. The serious robot had a voice with 20% more depth, based on voice personality stereotypes ( Metze, Black, and Polzehl 2011 ). In the second experiment, where all robots had a cheerful personality, the voice shaping and speed varied by 2–5% for each robot, so as to have an almost unnoticeable difference among the robots’ voices, especially during the robot-conversation session ( Polzehl, Moller, and Metze 2011 ).…”

Section: Methodsmentioning

confidence: 99%

Which One? Choosing Favorite Robot After Different Styles of Storytelling and Robots’ Conversation

2021

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The influence of human-care service robots in human–robot interaction is becoming of great importance, because of the roles that the robots are taking in today’s and future society. Thus, we need to identify how humans can interact, collaborate, and learn from social robots more efficiently. Additionally, it is important to determine the robots’ modalities that can increase the humans’ perceived likeness and knowledge acquisition and enhance human–robot collaboration. The present study aims to identify the optimal social service robots’ modalities that enhance the human learning process and level of enjoyment from the interaction and even attract the humans’ attention to choosing a robot to collaborate with it. Our target group was college students, pre-service teachers. For this purpose, we designed two experiments, each one split in two parts. Both the experiments were between groups, and human participants had the chance to watch the Nao robot performing a storytelling exercise about the history of robots in a museum-educational activity via video annotations. The robot’s modalities were manipulated on its body movements (expressive arm and head gestures) while performing the storytelling, friendly attitude expressions and storytelling, and personality traits. After the robot’s storytelling, participants filled out a knowledge acquisition questionnaire and a self-reported enjoyment level questionnaire. In the second part, we introduce the idea of participants witnessing a conversation between the robots with the different modalities, and they were asked to choose the robot with which they want to collaborate in a similar activity. Results indicated that participants prefer to collaborate with robots with a cheerful personality and expressive body movements. Especially when they were asked to choose between two robots that were cheerful and had expressive body movements, they preferred the one which originally told them the story. Moreover, participants did not prefer to collaborate with a robot with an extremely friendly attitude and storytelling style.

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