Search

Internet-of-Things technologies may help luxury companies deliver their offerings in a different way. However, their actual effects on consumers remain hazy. This paper sheds light on the impact that consumers' openness to technological innovations may have on perceived usefulness of Voice Assistants (VAs) in the context of luxury tourism. In two studies using luxury yachts and luxury hotels as research settings, we operationalised consumers' openness to technological innovations as risk propensity and openness to change, respectively, and examined their impact on consumers' perceived usefulness of VAs, considering the moderating role of status consumption orientation. Results showed that a greater level of openness to technological innovations leads consumers to perceive VAs as more useful, and this effect is mitigated when consumers exhibit greater status consumption orientation. [ABSTRACT FROM AUTHOR]

Copyright of Revista Iberoamericana de Ciencia, Tecnologia y Sociedad is the property of Centro de Estudios sobre Ciencia, Desarrollo y Educacion Superior and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Intelligent voice assistants, such as Apple Siri and Amazon Alexa, are widely used nowadays. These task-oriented dialogue systems require a semantic parsing module in order to process user utterances and understand the action to be performed. This semantic parsing component was initially implemented by rule-based or statistical slot-filling approaches for processing simple queries; however, the appearance of more complex utterances demanded the application of shift-reduce parsers or sequence-to-sequence models. Although shift-reduce approaches were initially considered the most promising option, the emergence of sequence-to-sequence neural systems has propelled them to the forefront as the highest-performing method for this particular task. In this article, we advance the research on shift-reduce semantic parsing for task-oriented dialogue. We implement novel shift-reduce parsers that rely on Stack-Transformers. This framework allows to adequately model transition systems on the transformer neural architecture, notably boosting shift-reduce parsing performance. Furthermore, our approach goes beyond the conventional top-down algorithm: we incorporate alternative bottom-up and in-order transition systems derived from constituency parsing into the realm of task-oriented parsing. We extensively test our approach on multiple domains from the Facebook TOP benchmark, improving over existing shift-reduce parsers and state-of-the-art sequence-to-sequence models in both high-resource and low-resource settings. We also empirically prove that the in-order algorithm substantially outperforms the commonly used top-down strategy. Through the creation of innovative transition systems and harnessing the capabilities of a robust neural architecture, our study showcases the superiority of shift-reduce parsers over leading sequence-to-sequence methods on the main benchmark. [ABSTRACT FROM AUTHOR]

Speaking in a second/foreign language, especially in English, is one of the most anxiety-provoking tasks for language learners. Anxiety provoked while speaking in a second language distresses the learners and further affects their oral proficiency in English. This article focuses on investigating the presence of anxiety among (n = 86) first-year Arts and Science students of a reputed university in India through Foreign Language Speaking Anxiety (FLSA) scale. The researchers tested the presence of anxiety pre and post-usage of Intelligent Personal Assistant (IPA) in Second Language (SL) classroom through the FLSA scale to deduce the impact of IPA-assisted language learning on speaking anxiety. Besides quantitative analysis, an in-depth interview was conducted with (n = 10) students to shed further insights on the significance of the study through qualitative inputs. Students who were interviewed voiced that they felt less anxious while conversing with IPA, and it paves way for ample practice and makes them feel comfortable while speaking in SL. The results revealed that the students had moderate to serious levels of anxiety in second language classrooms and the usage of IPA has significantly reduced their FLSA. [ABSTRACT FROM AUTHOR]

Voice Assistants (VAs), driven by Artificial Intelligence (AI), are gaining prominence and becoming increasingly relevant in various domains. Their distinctiveness lies in the incorporation of human-like attributes, setting them apart from conventional technologies and firmly situating them within the domain of Anthropomorphic Technologies (AT). This study aimed to comprehensively examine the impact of customers' gender, the gender of Anthropomorphic Voice Assistant (AVA), and the kind of relationship customers perceived to form with AVA on customers' attitudes toward AVA using an experimental design. [ABSTRACT FROM AUTHOR]

While voice user interfaces offer increased accessibility due to hands-free and eyes-free interactions, older adults often have challenges such as constructing structured requests and perceiving how such devices operate. Voice-first user interfaces have the potential to address these challenges by enabling multimodal interactions. Standalone voice + touchscreen Voice Assistants (VAs), such as Echo Show, are specific types of devices that adopt such interfaces and are gaining popularity. However, the affordances of the additional touchscreen for older adults are unknown. Through a 40-day real-world deployment with older adults living independently, we present a within-subjects study (N = 16; age M = 82.5, SD = 7.77, min. = 70, max. = 97) to understand how a built-in touchscreen might benefit older adults during device setup, conducting self-report diary survey, and general uses. We found that while participants appreciated the visual outputs, they still preferred to respond via speech instead of touch. We identified six design implications that can inform future innovations of senior-friendly VAs for managing healthcare and improving quality of life.

Purpose – This paper aims to understand how the perceived usefulness of voice assistants (VAs) is affected by the perceived quality of the process (interaction) and the outcome (information). The authors also aim to determine the extent to which the perceived usefulness of VAs improves the perceived privacy associated with their use and increases users’ intention to continue using them. Consumer technology innovativeness is included as a personal trait moderator, to compare the results between tech and nontech innovators. For this purpose, the authors use the framework of the uses and gratifications theory (U&GT). Design/methodology/approach – A survey of 467 VA users was conducted and structural equation modeling was used to analyze the data. Findings – The authors identify two main determinants of the perceived usefulness of VAs that influence users’ intention to continue using this technology, process quality and outcome quality. These two factors influence the continued use of VAs in different ways depending on the technology innovativeness of the consumers. The results show that tech innovators are oriented toward the interactive experience, and therefore, mainly value the process quality. In addition, nontech innovators are oriented toward a satisfactory response from VAs, and therefore, primarily value the outcome quality. In addition, the positive effect of perceived usefulness on perceived privacy is higher for tech innovators. Originality/value – This study enhances the literature on the perceived usefulness of VAs within the framework of U&GT. It identifies two antecedents (process quality and outcome quality) of perceived usefulness and observes significant differences based on technological innovativeness. Impacto de la calidad del proceso y resultado en la intención de seguir usando asistentes de voz Objetivo – Este artículo tiene como objetivo entender cómo la utilidad percibida de los Asistentes de Voz (AV) se ve afectada por la calidad percibida del proceso (interacción) y el resultado (información). Asimismo, busca determinar hasta qué punto la utilidad percibida de los AVs mejora la privacidad percibida asociada con su uso y, consecuentemente, la intención de los usuarios de seguir utilizándolos. La innovación tecnológica se incluye como moderador personal para comparar los resultados entre innovadores tecnológicos y no tecnológicos. Para este propósito, utilizamos la Teoría de Usos y Gratificaciones (U&GT). Diseño – Se realizó una encuesta a 467 usuarios de AVs, y se utilizó la modelización de ecuaciones estructurales (SEM) para analizar los datos. Resultados – La calidad del proceso y la calidad del resultado son antecedentes claros de la utilidad percibida de los AVs, que afecta a la intención de los usuarios de seguir usándolos. La influencia de ambos factores difiere entre usuarios según su nivel de innovación tecnológica. Los resultados muestran que los innovadores tecnológicos valoran más la experiencia interactiva y la calidad del proceso, mientras que los no innovadores tecnológicos se enfocan en obtener respuestas satisfactorias de los AVs. Además, la influencia positiva de la utilidad percibida en la privacidad percibida es más pronunciada en los innovadores tecnológicos. Originalidad – Este estudio enriquece la literatura sobre la utilidad percibida de los AVs dentro del marco de la U&GT. Identifica dos factores previos (calidad del proceso y calidad del resultado) de la utilidad percibida y observa diferencias significativas basadas en la innovación tecnológica. 过程和结果质量对继续使用语音助手意愿的影响 目的 – 本文旨在了解语音助手（VAs）的感知有用性如何受到过程（交互）和结果（信息）的感知质量的影响。我们还旨在确定语音助手的感知有用性在多大程度上改善了与使用语音助手相关的感知隐私, 并提高了用户继续使用语音助手的意愿。我们将消费者的技术创新性作为个人特质调节因素, 以比较技术创新者和非技术创新者的结果。为此, 我们使用了 “使用与满足理论"（U&GT）框架。 设计/方法/途径 – 我们对 467 名增值服务用户进行了调查, 并使用结构方程模型（SEM）对数据进行了分析。 研究结果 – 我们确定了影响用户继续使用该技术意向的虚拟机构感知有用性的两个主要决定因素：（1）过程质量和（2）结果质量。根据消费者的技术创新能力, 这两个因素以不同的方式影响着虚拟现实技术的持续使用。结果显示, 技术创新者以互动体验为导向, 因此主要看重过程质量。此外, 非技术创新者倾向于从虚拟机构获得令人满意的回应, 因此主要看重结果质量。此外, 对于科技创新者来说, 感知有用性对感知隐私的积极影响更大。 价值 – 本研究在 U&GT 框架内加强了有关虚拟机构感知有用性的文献。它确定了感知有用性的两个前因（过程质量和结果质量）, 并观察到了基于技术创新性的显著差异。

Abstract\nIMPLICATIONS FOR REHABILITATIONPurpose: This review aims to examine how the use of voice assistants influences loneliness in older adults.Materials and methods: This study follows the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Databases such as CINAHL, APA PsycINFO, MEDLINE, PubMed, Web of Science, ScienceDirect, Scopus, SciELO, Google Scholar, and IEEE Xplore were used. We implemented search strategies in English to locate studies published between January 2010 and January 2023, including those examining the impact of voice assistant usage on loneliness in older adults. Descriptive information was examined, assessing its quality with the Mixed Methods Appraisal Tool.Results: A total of 499 studies were yielded from the initial search, with 13 included in the final analysis. Positive outcomes in reducing loneliness were reported in 84.6% of these studies. There was a prevalence of quasi-experimental studies, alongside heterogeneous measurement instruments, scarce use of standardized tests, and small samples predominantly consisting of women. Commercial voice assistants were the most commonly utilized.Conclusions: Voice assistants show potential in mitigating feelings of loneliness in older adults. Adequate training and adaptation to specific needs seem essential to maximize their effectiveness. In particular, voice assistants available in the consumer market hold significant potential in this area. Further research is necessary to comprehend their impact, encompassing potential risks and ethical considerations.Effectively integrating voice assistants into day-to-day lives of older people can have a positive role on their psychological well-being and significantly contribute to improving their mental health by mitigating feelings of loneliness.Interventions incorporating voice assistants should focus on adapting to the specific needs of each individual. Adequate training and understanding needs are essential elements to maximize the effectiveness of these interventions.Given that most of the reviewed studies present small samples with a predominance of female participants, future initiatives should ensure that these interventions are equitable and beneficial for all demographic groups.Further research should focus on understanding and improving the accessibility of commercial voice assistants targeted at the general population. This involves ensuring that these technologies are easily adoptable by older adults through specific training and outreach strategies, which is especially important in the context of rehabilitation.Effectively integrating voice assistants into day-to-day lives of older people can have a positive role on their psychological well-being and significantly contribute to improving their mental health by mitigating feelings of loneliness.Interventions incorporating voice assistants should focus on adapting to the specific needs of each individual. Adequate training and understanding needs are essential elements to maximize the effectiveness of these interventions.Given that most of the reviewed studies present small samples with a predominance of female participants, future initiatives should ensure that these interventions are equitable and beneficial for all demographic groups.Further research should focus on understanding and improving the accessibility of commercial voice assistants targeted at the general population. This involves ensuring that these technologies are easily adoptable by older adults through specific training and outreach strategies, which is especially important in the context of rehabilitation. [ABSTRACT FROM AUTHOR]

This study aims to investigate how smartphone voice assistants (SVAs) impact brand engagement among Malaysian university students, who are leading in digital consumption trends. The study aims to investigate how brand characteristics such as appeal, attachment, perceived utility, and usability impact consumer behaviour by utilising Brand Identity and Technology Acceptance models. Analysed using structural equation modelling (SEM) in AMOS, data from 500 students experienced with voice assistants was collected through a survey. The results show strong connections in all studied relationships, emphasising the crucial importance of various brand attributes in promoting engagement. Usability and perceived utility are essential factors, indicating that businesses should focus on creating products that are both functional and user-friendly. The study provides distinctive perspectives on improving student engagement and brand partnerships in a competitive environment. It highlights the necessity for more research to help voice assistant professionals and academics enhance consumer-brand connections, especially among the digitally adept youth population in Malaysia. [ABSTRACT FROM AUTHOR]

Voice assistants (VAs), such as Alexa, Siri, or Google Now, are becoming increasingly ubiquitous. Consequently, the potential societal impacts of such systems are gaining relevance in public and academic discourses. Investigating the effects of VA voice features on user perception of VAs is one central aspect of research. Here, the potential effects of VAs on the perception of gender roles and the attribution of gender stereotypes stand out. Following the Computers as Social Actors paradigm, it is assumed that gendered voices have the potential to reproduce existing gender stereotypes. Yet, recently, the implementation of gender-ambiguous voices has been suggested to mitigate such effects and promote more diverse technology design. In this study, we set out to inquire about the relationship between gendered VA voice (male, female, gender-ambiguous) and gender stereotype activation. In two online surveys with an experimental manipulation (Study 1: N = 140, Study 2: N = 397), we test stereotype activation as a function of VA voice, user gender, and conversation topic. Empirical findings are mixed, with no effects for conversation topic but indications of small effects of VA voice. Implications for future research are discussed. [ABSTRACT FROM AUTHOR]

In an era where user experience reigns supreme, an unexpected element is subtly influencing our interactions with technology--"Cuteness." However, when discussing the design of digital products such as AIVAs, is cuteness merely a matter of appearance? This paper aims to unveil the complex psychological mechanisms and their impact on usage intention hidden behind the seemingly harmless allure of cuteness. Through an experimental study involving 284 participants and utilizing a moderated serial mediation model via PLS-SEM, this research reveals how aesthetic design differences influence usage intentions. The findings disclose three key insights: (1) A positive relationship between cuteness and usage intention is confirmed; (2) Social presence, performance expectancy and customer value act as serial mediations between cuteness and usage intention; (3) Perceived risk moderates the impact of cuteness on usage intentions by influencing social presence, performance expectancy, hedonic value and functional value. This contributes theoretical insights and practical guidance for the sustainable development and success of AIVAs. [ABSTRACT FROM AUTHOR]

This study integrates two lines of research: technologies as tools and technologies as social beings, under the theoretical framework of dynamic systems, to investigate the reciprocal dynamics between functional use and relational use of artificial intelligence (AI) voice assistants, and the mediating roles of self-disclosure and privacy concerns. A two-wave longitudinal survey was conducted among 354 AI voice assistant users across 2 months. Factor analysis results supported the conceptualization and operationalization of functional use and relational use of voice assistants. Results from the cross-lagged panel model confirmed that functional use and relational use reinforced themselves over time, respectively. Relational use increased subsequent functional use, and relational use reinforced itself through self-disclosure. Surprisingly, functional use did not increase subsequent relational use; instead, longitudinal mediation analysis showed that functional use reduced subsequent relational use due to the lack of self-disclosure. Furthermore, while self-disclosure increased subsequent privacy concerns, privacy concerns did not reduce subsequent self-disclosure. [ABSTRACT FROM AUTHOR]

This paper investigates the role of English in voice assistant (Siri, Alexa, Google Assistant) use from the perspective of language ideology. Major commercial companies in the voice assistant market use English as a training language for their speech technologies and offer the most optimised support for standardised varieties of English. This affects the experiences with voice assistants of speakers of non-European languages, i.e., one of the non-target audiences. Drawing on qualitative interview data from Turkish-speaking users who migrated to Germany, the present study reveals that the participants iconize English as the "standard" language in digital contexts, constructing it as the "original" language of speaking computers. By conducting an inductive analysis, the article demonstrates that not only the lack of technological support, but also specific discourses about Artificial Intelligence, impact perceptions of English. These developments have implications for our understandings of prestige and digital literacy in human-machine interactions. [ABSTRACT FROM AUTHOR]

The widespread use of voice assistants (VAs) creates a pressing need to understand what drives consumers to use different VAs. Existing studies have commonly focused on the net effects of antecedents that explain why consumers adopt or continue using VAs, ignoring the complexity of consumer behavior and the combinatorial effects of multiple antecedents. Our study proposes that consumer intention to continue using VAs does not depend on a single characteristic of products or consumers but on specific configurations of such characteristics. By integrating human–technology interaction and media richness theories, we suggest that consumers with distinct psychometric profiles and learning styles may evaluate humanlike and technological attributes of VAs differently. Our study shows that the complex interconnectedness between different VA attributes and consumer characteristics can provide a holistic understanding of why some consumers continue or stop using VAs. The results advance the media richness literature by offering novel insights into multimodality in consumer–technology interactions by examining consumer evaluations of single and multimodal VAs (e.g., smart speakers vs. touchscreen smart speakers). Our study provides templates for managers to effectively design VAs aligned with their segmentation and targeting strategies. [ABSTRACT FROM AUTHOR]

Voice Assistants have gained more attention in both real-life and academic fields thanks to their roles in the advanced world. This study aims to investigate the Behavioral Intention of Voice Assistants’ users by exploring the mediating role of Subjective Well-being and the moderating role of Innovativeness based on the Utilitarian and Gratification Theory framework. A quantitative study with structural equation modeling was carried out using SPSS and PLS-SEM software to analyze a sample of 230 Voice Assistant users. The findings illustrate that the Subjective Well-being of Voice Assistants’ users is influenced by Utilitarian benefits, Symbolic benefits and Social benefits. Behavioral intention is directly influenced by Utilitarian benefits, Hedonic benefits and Social benefits. The research establishes the moderating role of Innovativeness in the relationship of Subjective Well-being and Behavioral Intention. This study provides deeper insight into the motivations of Voice Assistants’ users from social and psychological viewpoints.

This paper develops a critical perspective on the use of conversational agents (CAs) with children at home. Drawing on interviews with eleven parents of pre-school children living in Norway, we illustrate the ways in which parents resisted the values epitomised by CAs. We problematise CAs' attributes in light of parents' ontological perceptions of what it means to be human and outline how their attitudes correspond to Bourdieu's [1998a. Acts of Resistance. New York: New Press] concept of acts of resistance. For example, parents saw artificial conversation designed for profit as a potential threat to users' autonomy and the instant gratification of CAs as a threat to children's development. Parents' antecedent beliefs map onto the ontological tensions between human and non-human attributes and challenge the neoliberal discourse by demanding freedom and equality for users rather than productivity and economic gain. Parents' comments reflect the belief that artificial conversation with a machine inappropriately and ineffectively mimics a nuanced and intimate human-to-human experience in service of profit motives. [ABSTRACT FROM AUTHOR]

Digital Voice Assistants (DVAs) have become a ubiquitous technology in today's home and childhood environments. Inspired by (Bernstein and Crowley, J Learn Sci 17:225–247, 2008) original study (n = 60, age 4–7 years) on how children's ontological conceptualizations of life and technology were systematically associated with their real-world exposure to robotic entities, the current study explored this association for children in their middle childhood (n = 143, age 7–11 years) and with different levels of DVA-exposure. We analyzed correlational survey data from 143 parent–child dyads who were recruited on 'Amazon Mechanical Turk' (MTurk). Children's ontological conceptualization patterns of life and technology were measured by asking them to conceptualize nine prototypical organically living and technological entities (e.g., humans, cats, smartphones, DVAs) with respect to their biology, intelligence, and psychology. Their ontological conceptualization patterns were then associated with their DVA-exposure and additional control variables (e.g., children's technological affinity, demographic/individual characteristics). Compared to biology and psychology, intelligence was a less differentiating factor for children to differentiate between organically living and technological entities. This differentiation pattern became more pronounced with technological affinity. There was some evidence that children with higher DVA-exposure differentiated more rigorously between organically living and technological entities on the basis of psychology. To the best of our knowledge, this is the first study exploring children's real-world exposure to DVAs and how it is associated with their conceptual understandings of life and technology. Findings suggest although psychological conceptualizations of technology may become more pronounced with DVA-exposure, it is far from clear such tendencies blur ontological boundaries between life and technology from children's perspective. [ABSTRACT FROM AUTHOR]

Purpose of Review: The present overview addresses the importance of voice in human-technology interactions within the sexual realm. It introduces empirical evidence within two key domains: (a) sexualized interactions involving artificial entities and (b) communication about sexuality-related health. Moreover, the review underscores existing research gaps. Recent Findings: Theories and first empirical studies underline the importance of voice within sexualized interactions with voice assistants or conversational agents as social cues. However, research on voice usage in sexual health-related contexts reveals contradicting results, mainly because these technologies ask users to vocalize potentially sensitive topics. Summary: Although the utilization of voice in technology is steadily advancing, the question of whether voice serves as the optimal medium for social interactions involving sexually related artificial entities and sexual health-related communication remains unanswered. This uncertainty stems from the fact that certain information must be conveyed verbally, which could also be communicated through alternative means, such as text-based interactions. [ABSTRACT FROM AUTHOR]

Internet-based cognitive behavioral therapy (iCBT) offers a scalable, cost-effective, accessible, and low-threshold form of psychotherapy. Recent advancements explored the use of conversational agents such as chatbots and voice assistants to enhance the delivery of iCBT. These agents can deliver iCBT-based exercises, recognize and track emotional states, assess therapy progress, convey empathy, and potentially predict longterm therapy outcome. However, existing systems predominantly utilize categorical approaches for emotional modeling, which can oversimplify the complexity of human emotional states. To address this, we developed a transformer-based model for dimensional text-based emotion recognition, fine-tuned with a novel, comprehensive dimensional emotion dataset comprising 75,503 samples. This model significantly outperforms existing state-of-the-art models in detecting the dimensions of valence, arousal, and dominance, achieving a Pearson correlation coefficient of r = 0.90, r = 0.77, and r = 0.64, respectively. Furthermore, a feasibility study involving 20 participants confirmed the model’s technical effectiveness and its usability, acceptance, and empathic understanding in a conversational agent-based iCBT setting, marking a substantial improvement in personalized and effective therapy experiences. [ABSTRACT FROM AUTHOR]

This study investigates the factors that build resistance and attitude towards AI voice assistants (AIVA). A theoretical model is proposed using the dual-factor framework by integrating status quo bias factors (sunk cost, regret avoidance, inertia, perceived value, switching costs, and perceived threat) and Technology Acceptance Model (TAM; perceived ease of use and perceived usefulness) variables. The study model investigates the relationship between the status quo factors and resistance towards adoption of AIVA, and the relationship between TAM factors and attitudes towards AIVA. A sample of four hundred and twenty was analysed using structural equation modeling to investigate the proposed hypotheses. The results indicate an insignificant relationship between inertia and resistance to AIVA. Perceived value was found to have a negative but significant relationship with resistance to AIVA. Further, the study also found that inertia significantly differs across gender (male/female) and age groupings. The study's framework and results are posited as adding value to the extant literature and practice, directly related to status quo bias theory, dual-factor model and TAM. [ABSTRACT FROM AUTHOR]

Copyright of HMD: Praxis der Wirtschaftsinformatik is the property of Springer Nature and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Voice assistants are increasingly prevalent, from personal devices to team environments. This study explores how voice type and contribution quality influence human–agent team performance and perceptions of anthropomorphism, animacy, intelligence, and trustworthiness. By manipulating both, we reveal mechanisms of perception and clarify ambiguity in previous work. Our results show that the human resemblance of a voice assistant’s voice negatively interacts with the helpfulness of an agent’s contribution to flip its effect on perceived anthropomorphism and perceived animacy. This means human teammates interpret the agent’s contributions differently depending on its voice. Our study found no significant effect of voice on perceived intelligence, trustworthiness, or team performance. We find differences in these measures are caused by manipulating the helpfulness of an agent. These findings suggest that function matters more than form when designing agents for high-performing human–agent teams, but controlling perceptions of anthropomorphism and animacy can be unpredictable even with high human resemblance.

This study investigates the ability of voice assistants and generative AI tools to respond to reference questions traditionally received by academic librarians. The authors created a sample of 25 questions based on queries received on the virtual reference service at their institution. They then created a rubric to evaluate the quality of the answers that the AI powered tools provided. The authors determined that the tools understand reference questions well and provide relevant answers but that the quality of the references provided, and the accuracy of the answers can be lacking. They suggest that more research needs to be done to understand the place of AI powered tools in reference services. [ABSTRACT FROM AUTHOR]

Introduction: Voice assistants (VAs) have the potential to uphold and enhance the quality of life for older adults. However, the extent to which older adults accept and benefit from VAs may be relatively modest. Methods: This study developed a comprehensive model combined with product and personal characteristics to explain the acceptance of VAs among older adults, using semi-structured interviews (Study 1) and questionnaires (Study 2). Results: Results revealed that in terms of product characteristics, perceived usefulness and perceived enjoyment significantly affect behavior intention. Regarding personal characteristics of older adults, technological self-efficacy and dispositional resistance to change significantly affect behavior intention. However, no direct impact of perceived ease of use and perceived trust on behavior intention. Additionally, perceived enjoyment influenced both perceived ease of use and perceived usefulness. Discussion: Results suggested the significant role of technology self-efficacy and dispositional resistance to change in predicting the acceptance of VAs among older adults. Our newly developed model offers valuable insights for tailoring VAs to this demographic during design and implementation. [ABSTRACT FROM AUTHOR]

In recent years, user experience (UX) has gained importance in the field of interactive systems. To ensure its success, interactive systems must be evaluated. As most of the standardized evaluation tools are dedicated to graphical user interfaces (GUIs), the evaluation of voice-based interactive systems or voice user interfaces is still in its infancy. With the help of a well-established evaluation scale, the System Usability Scale (SUS), two prominent, widely accepted voice assistants were evaluated. The evaluation, with SUS, was conducted with 16 participants who performed a set of tasks on Amazon Alexa Echo Dot and Google Nest Mini. We compared the SUS score of Amazon Alexa Echo Dot and Google Nest Mini. Furthermore, we derived the confidence interval for both voice assistants. To enhance understanding for usability practitioners, we analyzed the Adjective Rating Score of both interfaces to comprehend the experience of an interface's usability through words rather than numbers. Additionally, we validated the correlation between the SUS score and the Adjective Rating Score. Finally, a paired sample t-test was conducted to compare the SUS score of Amazon Alexa Echo Dot and Google Nest Mini. This resulted in a huge difference in scores. Hence, in this study, we corroborate the utility of the SUS in voice user interfaces and conclude by encouraging researchers to use SUS as a usability metric to evaluate voice user interfaces. [ABSTRACT FROM AUTHOR]

Internet-based cognitive behavioral therapy (iCBT) offers a scalable, cost-effective, accessible, and low-threshold form of psychotherapy. Recent advancements explored the use of conversational agents such as chatbots and voice assistants to enhance the delivery of iCBT. These agents can deliver iCBT-based exercises, recognize and track emotional states, assess therapy progress, convey empathy, and potentially predict long-term therapy outcome. However, existing systems predominantly utilize categorical approaches for emotional modeling, which can oversimplify the complexity of human emotional states. To address this, we developed a transformer-based model for dimensional text-based emotion recognition, fine-tuned with a novel, comprehensive dimensional emotion dataset comprising 75,503 samples. This model significantly outperforms existing state-of-the-art models in detecting the dimensions of valence, arousal, and dominance, achieving a Pearson correlation coefficient of r = 0.90, r = 0.77, and r = 0.64, respectively. Furthermore, a feasibility study involving 20 participants confirmed the model’s technical effectiveness and its usability, acceptance, and empathic understanding in a conversational agent-based iCBT setting, marking a substantial improvement in personalized and effective therapy experiences.

Voice assistants (VAs) are increasingly integrated into everyday activities and tasks, raising novel challenges for users and researchers. One emergent research direction concerns proactive VAs, who can initiate interaction without direct user input, offering unique benefits including efficiency and natural interaction. Yet, there is a lack of review studies synthesizing the current knowledge on how proactive behavior has been implemented in VAs and under what conditions proactivity has been found more or less suitable. To this end, we conducted a systematic review following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist. We searched for articles in the ACM Digital Library, IEEExplore, and PubMed, and included primary research studies reporting user evaluations of proactive VAs, resulting in 21 studies included for analysis. First, to characterize proactive behavior in VAs we developed a novel conceptual model encompassing context, initiation, and action components: Activity/status emerged as the primary contextual element, direct initiation was more common than indirect initiation, and suggestions were the primary action observed. Second, proactive behavior in VAs was predominantly explored in domestic and in-vehicle contexts, with only safety-critical and emergency situations demonstrating clear benefits for proactivity, compared to mixed findings for other scenarios. The paper concludes with a summary of the prevailing knowledge gaps and potential research avenues.

Abstract Background Patient-reported outcome (PRO) measures provide valuable evidence in clinical trials; however, poor compliance with PRO measures is a notable and long-standing problem, resulting in missing data that potentially impact the interpretation of trial results. Interactive, patient-centric platforms may increase participants’ motivation to complete PRO measures over the course of a clinical trial. Thus, the aim of this study was to evaluate and optimize the usability of 3 popular consumer technologies—a traditional app-based interface, a chatbot interface, and a speech-operated interface—that may be used to improve user engagement and compliance with PRO measures. Methods Participants aged 18–75 years from the general United States population tested the usability of 3 ePRO platforms: a traditional app-based interface using Datacubed Health Platform (Datacubed), a web-based chatbot interface using the Orbita platform, and a speech-operated Alexa interface using an Alexa Skill called “My Daily Wellness.” The usability of these platforms was tested with 2 PRO measures: the EQ-5D-5 L and the SF-12v2 Health Survey (SF-12v2), Daily recall. Using a crossover design, 3 cohorts of participants tested each ePRO platform daily for 1 week. After testing, interviews were conducted regarding the participants’ experience with each platform. Results A total of 24 adults participated in the study. The mean age of participants was 45 years (range, 21–71 years), and half were female (n = 12; 50%). Overall, participants prioritized speed, ease of use, and device portability in selecting their preferred platform. The Datacubed app met these criteria and was the preferred platform among most participants (n = 20; 83%). Participants also suggested various modifications to the platforms, such as programmable notifications, adjustable speed, and additional daily reminders. Conclusions These data demonstrate the importance of speed, ease of use, and device portability, features that are currently incorporated in the Datacubed app, in ePRO platforms used in future clinical trials. Additionally, the usability of ePRO platforms may be optimized by adding programmable notifications, adjustable speed, and increased daily reminders. The results of this study may be used to enhance the usability and patient centricity of these platforms to improve user compliance and engagement during clinical trials.