"Siri Talks at You"

Abdolrahmani, Ali; Kuber, Ravi; Branham, Stacy M.

doi:10.1145/3234695.3236344

Cited by 100 publications

(66 citation statements)

References 24 publications

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“…As VAPAs have rapidly become pervasive in the home (as smart speakers) and on-the-go (as mobile apps), researchers have started to examine their feasibility for various populations. These include infrequent and frequent users [10,22], native and non-native English-speaking users [32], low-income and middle-income users [4], as well as older adults and people with disabilities (e.g., [1,3,10,29,37]). Our study focuses on VAPA feasibility for people who are blind.…”

Section: Related Workmentioning

confidence: 99%

Section: Trust and Privacymentioning

confidence: 99%

“…Trust and privacy are identified across user groups as being a pervasive concern affecting adoption of VAPAs in daily life [1,4,11,19,22]. Speech recognition errors are known to degrade user trust [1]. While these errors are the most frequent obstacle, prior research shows this can be mitigated by implementing a "read" back feature, which helps users create an accurate mental model of the error and how to address it [26].…”

Section: Trust and Privacymentioning

confidence: 99%

“…active monthly users of mobile voice assistants and 45.7 million users of smart speakers [23]. There has been significant recent interest among HCI researchers regarding these technologies [4,11,20,22,23,29,31,32,38], with several studies that include perspectives of older adults [28,38,40] and people with disabilities [1,3,7,29,37]. Blind users comprise a large minority customer base of technologies like Amazon Echo, despite the presence of accessibility and usability challenges for this population [1,29].…”

Section: Introductionmentioning

confidence: 99%

“…There has yet to be a systematic analysis of how VAPA designers conceptualize the ideal system--its goals, user needs, and interaction metaphors. Commercial VAPA guidelines stand to offer a unique window into how the developed systems operate and may allow us to pinpoint fundamental sources of documented accessibility and usability issues [1,29].…”

Section: Introductionmentioning

confidence: 99%

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Reading Between the Guidelines

Branham

Roy

2019

The 21st International ACM SIGACCESS Conference on Computers and Accessibility

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Voice-Activated Personal Assistants (VAPAs)-like Apple Siri and Amazon Alexa-have rapidly become common features on mobile devices and in homes of millions of people around the world. They have proven to be particularly valuable to people with disabilities, chiefly among people with visual impairments. Yet, we still know relatively little about the fundamental metaphors and guidelines for designing voice assistants, and how they might empower and constrain visually impaired users. To address this need, we conducted a qualitative document review of VAPA design guidelines published by top commercial vendors Amazon, Google, Microsoft, Apple and Alibaba. We found that guidelines have many commonalities that surface an underlying assumption that VAPA interfaces should be modeled after human-human conversation. We draw on prior work about needs of people with visual impairments to critique this taken-for-granted human-human conversation metaphor and offer amendments to prevailing design guidelines that can make this now-pervasive platform more fully achieve its potential to become universally usable.

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Section: Related Workmentioning

confidence: 99%

Section: Trust and Privacymentioning

confidence: 99%

Section: Trust and Privacymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reading Between the Guidelines

Branham

Roy

2019

The 21st International ACM SIGACCESS Conference on Computers and Accessibility

Self Cite

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Understanding voice‐based information uncertainty: A case study of health information seeking with voice assistants

Brewer

2023

Asso for Info Science & Tech

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Evaluating information quality online is increasingly important for healthy decision‐making. People assess information quality using visual interfaces (e.g., computers, smartphones) with visual cues like aesthetics. Yet, voice interfaces lack critical visual cues for evaluating information because there is often no visual display. Without ways to assess voice‐based information quality, people may overly trust or misinterpret information which can be challenging in high‐risk or sensitive contexts. This paper investigates voice information uncertainty in one high‐risk context—health information seeking. We recruited 30 adults (ages 18–84) in the United States to participate in scenario‐based interviews about health topics. Our findings provide evidence of information uncertainty expectations with voice assistants, voice search preferences, and the audio cues they use to assess information quality. We contribute a nuanced discussion of how to inform more critical information ecosystems with voice technologies and propose ways to design audio cues to help people more quickly assess content quality.

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