Compared to traditional industrial robots that are often designed to perform dull, dangerous, and dirty jobs by replacing human beings, social robots are made to interact closely with humans in collaborative contexts (Broadbent, 2017). The last 20 years have seen a steady growth in the development of social robots. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.ĭiscussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice.
This latter point was only applicable to one of the synthesized voices. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. Contrary to the expectations of an uncanny valley, when the ratings of human-likeness for both the voice and the speaker characteristics were higher, they seemed less eerie to the participants. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. Females rated synthesized voices more positively on most dimensions. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Methods: 95 adults (62 females) listened to randomly presented audio-clips of three categories: synthesized ( Watson, IBM), humanoid (robot Sophia, Hanson Robotics), and human voices (five clips/category).
Little is known about human perception of synthesized voices.Īim: To investigate which synthesized voice parameters predict the speaker's eeriness and voice likability to determine if individual listener characteristics (e.g., personality, attitude toward robots, age) influence synthesized voice evaluations and to explore which paralinguistic features subjectively distinguish humans from robots/artificial agents. Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots.
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