Speak to me and I tell you who you are! A language-attitude study in a cultural-heritage application (original) (raw)
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Social Evaluation of Artificial Agents by Language Varieties
Intelligent Virtual Agents, 2012
In Sociolinguistics, language attitude studies based on natural voices have provided evidence that human listeners socially assess and evaluate their communication partners according to the language variety they use. Similarly, research on intelligent agents has demonstrated that the degree an artificial entity resembles a human correlates with the likelihood that the entity will evoke social and psychological processes in humans. Taking the two findings together, we hypothesize that synthetically generated language varieties have social effects similar to those reported from language attitude studies on natural speech. We present results from a language-attitude study based on three synthetic varieties of Austrian German. Our results on synthetic speech are in accordance with previous findings from natural speech. In addition, we show that language variety together with voice quality of the synthesized speech bring about attributions of different social aspects and stereotypes and influence the attitudes of the listeners toward the artificial speakers.
Social evaluation of artificial agents by language
2013
In Sociolinguistics, language attitude studies based on natural voices have provided evidence that human listeners socially assess and evaluate their communication partners according to the language variety they use. Similarly, research on intelligent agents has demonstrated that the degree an artificial entity resembles a human correlates with the likelihood that the entity will evoke social and psychological processes in humans. Taking the two findings together, we hypothesize that synthetically generated language varieties have social effects similar to those reported from language attitude studies on natural speech. We present results from a language-attitude study based on three synthetic varieties of Austrian German. Our results on synthetic speech are in accordance with previous findings from natural speech. In addition, we show that language variety together with voice quality of the synthesized speech bring about attributions of different social aspects and stereotypes and influence the attitudes of the listeners toward the artificial speakers.
Effects of Language Variety on Personality Perception in Embodied Conversational Agents
Lecture Notes in Computer Science, 2014
In this paper, we investigate the effects of language variety in combination with bodily behaviour on the perceived personality of a virtual agent. In particular, we explore changes on the extroversion-introversion dimension of personality. An online perception study was conducted featuring a virtual character with different levels of expressive body behaviour and different synthetic voices representing German and Austrian language varieties. Clear evidence was found that synthesized language variety, and gestural expressivity influence the human perception of an agent's extroversion. Whereby Viennese and Austrian standard language are perceived as more extrovert than it is the case for the German standard.
Forming social impressions from voices in native and foreign languages
Scientific Reports, 2019
We form very rapid personality impressions about speakers on hearing a single word. This implies that the acoustical properties of the voice (e.g., pitch) are very powerful cues when forming social impressions. Here, we aimed to explore how personality impressions for brief social utterances transfer across languages and whether acoustical properties play a similar role in driving personality impressions. Additionally, we examined whether evaluations are similar in the native and a foreign language of the listener. In two experiments we asked Spanish listeners to evaluate personality traits from different instances of the Spanish word “Hola” (Experiment 1) and the English word “Hello” (Experiment 2), native and foreign language respectively. The results revealed that listeners across languages form very similar personality impressions irrespective of whether the voices belong to the native or the foreign language of the listener. A social voice space was summarized by two main perso...
The Impact of Linguistic and Cultural Congruity on Persuasion by Conversational Agents
Lecture Notes in Computer Science, 2010
We present an empirical study on the impact of linguistic and cultural tailoring of a conversational agent on its ability to change user attitudes. We designed two bilingual (English and Spanish) conversational agents to resemble members of two distinct cultures (Anglo-American and Latino) and conducted the study with participants from the two corresponding populations. Our results show that cultural tailoring and participants' personality traits have a significant interaction effect on the agent's persuasiveness and perceived trustworthiness.
Interspeech 2020, 2020
More and more, humans are engaging with voice-activated artificially intelligent (voice-AI) systems that have names (e.g., Alexa), apparent genders, and even emotional expression; they are in many ways a growing 'social' presence. But to what extent do people display sociolinguistic attitudes, developed from human-human interaction, toward these disembodied text-tospeech (TTS) voices? And how might they vary based on the cognitive traits of the individual user? The current study addresses these questions, testing native English speakers' judgments for 6 traits (intelligent, likeable, attractive, professional, human-like, and age) for a naturally-produced female human voice and the US-English default Amazon Alexa voice. Following exposure to the voices, participants completed these ratings for each speaker, as well as the Autism Quotient (AQ) survey, to assess individual differences in cognitive processing style. Results show differences in individuals' ratings of the likeability and human-likeness of the human and AI talkers based on AQ score. Results suggest that humans transfer social assessment of human voices to voice-AI, but that the way they do so is mediated by their own cognitive characteristics.
Human Communication Research, 2007
Computer-generated anthropomorphic characters are a growing type of communicator that is deployed in digital communication environments. An essential theoretical question is how people identify humanlike but clearly artificial, hence humanoid, entities in comparison to natural human ones. This identity categorization inquiry was approached under the framework of consistency and tested through examining inconsistency effects from mismatching categories. Study 1 (N = 80), incorporating a self-disclosure task, tested participants' responses to a talking-face agent, which varied in four combinations of human versus humanoid faces and voices. In line with the literature on inconsistency, the pairing of a human face with a humanoid voice or a humanoid face with a human voice led to longer processing time in making judgment of the agent and less trust than the pairing of a face and a voice from either the human or the humanoid category. Female users particularly showed negative attitudes toward inconsistently paired talking faces. Study 2 (N = 80), using a task that stressed comprehension demand, replicated the inconsistency effects on judging time and females' negative attitudes but not for comprehension-related outcomes. Voice clarity overshadowed the consistency concern for comprehension-related responses. The overall inconsistency effects suggest that people treat humanoid entities in a different category from natural human ones.
Scientific Reports
There is growing concern that artificial intelligence conversational agents (e.g., Siri, Alexa) reinforce voice-based social stereotypes. Because little is known about social perceptions of conversational agents’ voices, we investigated (1) the dimensions that underpin perceptions of these synthetic voices and (2) the role that acoustic parameters play in these perceptions. Study 1 (N = 504) found that perceptions of synthetic voices are underpinned by Valence and Dominance components similar to those previously reported for natural human stimuli and that the Dominance component was strongly and negatively related to voice pitch. Study 2 (N = 160) found that experimentally manipulating pitch in synthetic voices directly influenced dominance-related, but not valence-related, perceptions. Collectively, these results suggest that greater consideration of the role that voice pitch plays in dominance-related perceptions when designing conversational agents may be an effective method for ...
International Journal of Human-Computer Studies, 2006
There is evidence that people react more positively when they are presented with faces that are consistent with their voices. Nass and Brave [2005]. Wired for speech: How voice Activates and Advances the Human-computer Relationship. MIT Press, Cambridge, MA] found that computerized and human faces were perceived more positively when paired, respectively, with synthesized versus human voices than when paired with inconsistent voices. The present study sought to examine whether this type of inconsistency would effect perceptions of persuasive messages delivered by humans versus computers. We created a situation in which reactions to computer synthesized speech were compared to human speech when the speech was either from a person or a computer. This paper presents two studies, one using audio taped stimuli and one using videotaped stimuli, with type of speech (human versus computer synthesized) manipulated factorially with source (person versus computer). As hypothesized, both studies suggest that in the human as source condition, human voice is perceived more favorably than synthetic voice. However, in the computer as source condition, both human and computer voice were rated similarly. We discuss these findings in terms of consistency as well as group processes effects that may be occurring. r