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The Human Takes It All
(2020)
Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.
Aim: 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.
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). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.
Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. 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. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.
Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.
The Human Takes It All
(2020)
Background: The increasing involvement of social robots in human lives raises the question as to how humans perceive social robots. Little is known about human perception of synthesized voices.
Aim: 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.
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). Voices were rated on intelligibility, prosody, trustworthiness, confidence, enthusiasm, pleasantness, human-likeness, likability, and naturalness. Speakers were rated on appeal, credibility, human-likeness, and eeriness. Participants' personality traits, attitudes to robots, and demographics were obtained.
Results: The human voice and human speaker characteristics received reliably higher scores on all dimensions except for eeriness. Synthesized voice ratings were positively related to participants' agreeableness and neuroticism. Females rated synthesized voices more positively on most dimensions. Surprisingly, interest in social robots and attitudes toward robots played almost no role in voice evaluation. 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. Moreover, when the speaker's voice was more humanlike, it was more liked by the participants. This latter point was only applicable to one of the synthesized voices. Finally, pleasantness and trustworthiness of the synthesized voice predicted the likability of the speaker's voice. Qualitative content analysis identified intonation, sound, emotion, and imageability/embodiment as diagnostic features.
Discussion: Humans clearly prefer human voices, but manipulating diagnostic speech features might increase acceptance of synthesized voices and thereby support human-robot interaction. There is limited evidence that human-likeness of a voice is negatively linked to the perceived eeriness of the speaker.
In numerical processing, the functional role of Spatial-Numerical Associations (SNAs, such as the association of smaller numbers with left space and larger numbers with right space, the Mental Number Line hypothesis) is debated. Most studies demonstrate SNAs with lateralized responses, and there is little evidence that SNAs appear when no response is required. We recorded passive holding grip forces in no-go trials during number processing. In Experiment 1, participants performed a surface numerical decision task (“Is it a number or a letter?”). In Experiment 2, we used a deeper semantic task (“Is this number larger or smaller than five?”). Despite instruction to keep their grip force constant, participants' spontaneous grip force changed in both experiments: Smaller numbers led to larger force increase in the left than in the right hand in the numerical decision task (500–700 ms after stimulus onset). In the semantic task, smaller numbers again led to larger force increase in the left hand, and larger numbers increased the right-hand holding force. This effect appeared earlier (180 ms) and lasted longer (until 580 ms after stimulus onset). This is the first demonstration of SNAs with passive holding force. Our result suggests that (1) explicit motor response is not a prerequisite for SNAs to appear, and (2) the timing and strength of SNAs are task-dependent. (216 words).
In numerical processing, the functional role of Spatial-Numerical Associations (SNAs, such as the association of smaller numbers with left space and larger numbers with right space, the Mental Number Line hypothesis) is debated. Most studies demonstrate SNAs with lateralized responses, and there is little evidence that SNAs appear when no response is required. We recorded passive holding grip forces in no-go trials during number processing. In Experiment 1, participants performed a surface numerical decision task (“Is it a number or a letter?”). In Experiment 2, we used a deeper semantic task (“Is this number larger or smaller than five?”). Despite instruction to keep their grip force constant, participants' spontaneous grip force changed in both experiments: Smaller numbers led to larger force increase in the left than in the right hand in the numerical decision task (500–700 ms after stimulus onset). In the semantic task, smaller numbers again led to larger force increase in the left hand, and larger numbers increased the right-hand holding force. This effect appeared earlier (180 ms) and lasted longer (until 580 ms after stimulus onset). This is the first demonstration of SNAs with passive holding force. Our result suggests that (1) explicit motor response is not a prerequisite for SNAs to appear, and (2) the timing and strength of SNAs are task-dependent. (216 words).
Finger-based numerical representations have gained increasing research interest. However, their description and assessment often refer to different numerical principles of ordinality, cardinality and 1-to-1 correspondence. Our aim was to investigate similarities and differences between these principles in finger-based numerical representations. Sixty-eight healthy adults performed ordinal finger counting, cardinal finger montring (showing the number of gestures) and finger-to-number mapping with twisted arms and fingers. We found that counting gestures and montring postures were identical for Number 10 but differed to varying degrees for other numbers. Interestingly, there was no systematic relation between finger-to-number mapping and ordinal finger counting habits. These data question the assumption of a unitary embodied finger-based numerical representation, but suggest that different finger-based representations co-exist and can be recruited flexibly depending on the numerical aspects to be conveyed.
Die nun begonnene Reihe „studieren++“ resultiert aus einer von der Universität Potsdam angebotenen Vorlesungsreihe. Das Besondere an dieser Vorlesungsreihe ist der multidisziplinäre Anspruch und die konsequent umgesetzte Zusammenarbeit über Disziplingrenzen hinweg. Die nicht nur über Instituts-, sondern über Fakultätsgrenzen praktizierte Interdisziplinarität erlaubt die Betrachtung eines Problems oder Sachverhalts aus unterschiedlichen Blickwinkeln. Wissenschaftliche Fragestellungen sind komplex und nicht immer auf eine Disziplin beschränkt. Sie in ihrer Gänze erfassen und nachhaltige Lösungsstrategien oder Konzepte entwickeln zu können gelingt oft nur durch eine multidisziplinäre Kooperation. Eine Lehrveranstaltung wie die vorliegende ist nicht nur für die Studierenden einer Universität eine hervorragende Möglichkeit, um über die Grenzen der eigenen Disziplin hinaus zu blicken und die Zusammenarbeit mit Wissenschaftlerinnen und Wissenschaftlern aus anderen Bereichen zu pflegen. So lernt man, sich in andere Sichtweisen hineinzuversetzen und sich zwischen den Disziplinen zu bewegen – eine Kompetenz, die in der hochkomplexen Arbeitswelt von heute von hohem Nutzen ist.
Der vorliegende erste Band der Reihe hat „Raum und Zahl“ zum Thema und ist aus einer Ringvorlesung aus dem Wintersemester 2013/2014 entstanden. Drei der fünf Fakultäten, insgesamt neun Institute der Universität Potsdam, haben sich an der Vorlesung beteiligt und sich dieses spannenden Themas angenommen. Als jemand, der sich jahrelang wissenschaftlich mit algorithmischer Geometrie sowie mit raumbezogenen Datenbanken und Navigationssystemen beschäftigt hat, kann ich nur bekräftigen, dass die Bezüge zwischen Raum und Zahl, zwischen Räumen und Zahlen, noch viel stärker im öffentlichen Bewusstsein verankert gehören. Räume auch quantitativ zu erfassen und zu verstehen ist eine Kulturtechnik, die an Wichtigkeit eher noch zunimmt, vor allem vor dem Hintergrund, dass wir genetisch nicht allzu gut auf derartige Herausforderungen vorbereitet sind. Denn viele unserer einschlägigen Gene entstammen noch aus der Zeit der Savanne, einer Zeit, zu der das Raumkonzept sich fast ausschließlich auf die unmittelbare räumliche Umgebung bezog und Zahlen jenseits von 10 nur wenig Relevanz für das eigene Überleben hatten.
Als Präsident der Universität Potsdam freut es mich ganz besonders, dass sich die hier vertretenen Wissenschaftler bereit erklärt haben, ihre Überlegungen mit den Studierenden und ihren Kolleginnen und Kollegen zu teilen. Herrn Kollegen Hans-Joachim Petsche möchte ich für sein Engagement danken und ihm zu dieser gelungenen Reihe gratulieren. Der Geist der Wissenschaft, der nicht nur einsam im Büro oder Labor gelebt wird, sondern gerade an einer Universität auch aktiv nach außen getragen werden sollte, wird hier in besonderer Weise sichtbar. Ich wünsche Ihnen viel Freude bei der Lektüre des Bandes und freue mich auf weitere Veröffentlichungen in dieser Reihe.
What features of a poem make it captivating, and which cognitive mechanisms are sensitive to these features? We addressed these questions experimentally by measuring pupillary responses of 40 participants who listened to a series of Limericks. The Limericks ended with either a semantic, syntactic, rhyme or metric violation. Compared to a control condition without violations, only the rhyme violation condition induced a reliable pupillary response. An anomaly-rating study on the same stimuli showed that all violations were reliably detectable relative to the control condition, but the anomaly induced by rhyme violations was perceived as most severe. Together, our data suggest that rhyme violations in Limericks may induce an emotional response beyond mere anomaly detection.
Language and Arithmetic
(2018)
We examined cross-domain semantic priming effects between arithmetic and language. We paired subtractions with their linguistic equivalent, exception phrases (EPs) with positive quantifiers (e.g., “everybody except John”) while pairing additions with their own linguistic equivalent, EPs with negative quantifiers (e.g., “nobody except John”; Moltmann, 1995). We hypothesized that EPs with positive quantifiers prime subtractions and inhibit additions while EPs with negative quantifiers prime additions and inhibit subtractions. Furthermore, we expected similar priming and inhibition effects from arithmetic into semantics. Our design allowed for a bidirectional analysis by using one trial's target as the prime for the next trial. Two experiments failed to show significant priming effects in either direction. Implications and possible shortcomings are explored in the general discussion.
Language and Arithmetic
(2018)
We examined cross-domain semantic priming effects between arithmetic and language. We paired subtractions with their linguistic equivalent, exception phrases (EPs) with positive quantifiers (e.g., “everybody except John”) while pairing additions with their own linguistic equivalent, EPs with negative quantifiers (e.g., “nobody except John”; Moltmann, 1995). We hypothesized that EPs with positive quantifiers prime subtractions and inhibit additions while EPs with negative quantifiers prime additions and inhibit subtractions. Furthermore, we expected similar priming and inhibition effects from arithmetic into semantics. Our design allowed for a bidirectional analysis by using one trial's target as the prime for the next trial. Two experiments failed to show significant priming effects in either direction. Implications and possible shortcomings are explored in the general discussion.