Viral Spread via Entertainment and Voice-Messaging Among Telephone Users in India

Raza, Agha Ali; Kulshreshtha, Rajat; Gella, Spandana; Blagsvedt, Sean; Chandrasekaran, Maya; Raj, Bhiksha; Rosenfeld, Roni

doi:10.1145/2909609.2909669

Cited by 18 publications

(6 citation statements)

References 22 publications

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“…Interestingly, the demographics of identifiable 5 users of the systems were are dominated by adult males (59 %) and children (38 %), with adult females accounting for just 3 % of the analysed interactions. These findings replicate gender imbalances of IVR systems, such as Sangeet Swara [26] and Polly [19,20], which were both primarily used by men.…”

Section: Resultssupporting

confidence: 71%

StreetWise

Pearson

Robinson

Reitmaier

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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This paper explores the use of conversational speech question and answer systems in the challenging context of public spaces in slums. A major part of this work is a comparison of the source and speed of the given responses; that is, either machine-powered and instant or human-powered and delayed. We examine these dimensions via a two-stage, multi-sited deployment. We report on a pilot deployment that helped refine the system, and a second deployment involving the installation of nine of each type of system within a large Mumbai slum for a 40-day period, resulting in over 12,000 queries. We present the findings from a detailed analysis and comparison of the two question-answer corpora; discuss how these insights might help improve machine-powered smart speakers; and, highlight the potential benefits of multi-sited public speech installations within slum environments. CCS CONCEPTS• Information systems → Speech / audio search; • Humancentered computing → Field studies; Interaction paradigms; Sound-based input / output; Interaction techniques.

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Section: Resultssupporting

confidence: 71%

StreetWise

Pearson

Robinson

Reitmaier

et al. 2019

Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems

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“…Turning first to the people who used the TalkBack system. Our findings reproduce those of emergent user studies in India and Pakistan of IVR systems [29,35] as well as smart speaker studies [5,26] in that women-as far as we could tell in our analysis-were in the minority of users (4 %). Future work should focus on their non-use [32] and, if appropriate, could pivot back into the home where female users in Bhalla's study indicated they prefer to use mobile voice assistants [5].…”

Section: Limitations and Future Worksupporting

confidence: 87%

“…Typically seen as an annoyance by mainstream users contacting customer service departments of businesses such as banks or mobile operators, IVR systems that allow users to create and share their own content have been tremendously popular elsewhere, particularly in India and Pakistan. For instance, Polly [29], which emphasises viral information spread, has been used extensively for entertainment and social contact in Pakistan. Sangeet Swara, the IVR equivalent of an internet forum, has been used by rural communities in India for songs, poems, jokes and cultural content [35].…”

Section: Voice User Interfaces In Resource-constrained Settingsmentioning

confidence: 99%

An Honest Conversation: Transparently Combining Machine and Human Speech Assistance in Public Spaces

Reitmaier

Robinson

Pearson

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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There is widespread concern over the ways speech assistant providers currently use humans to listen to users' queries without their knowledge. We report two iterations of the Talk-Back smart speaker, which transparently combines machine and human assistance. In the first, we created a prototype to investigate whether people would choose to forward their questions to a human answerer if the machine was unable to help. Longitudinal deployment revealed that most users would do so when given the explicit choice. In the second iteration we extended the prototype to draw upon spoken answers from previous deployments, combining machine efficiency with human richness. Deployment of this second iteration shows that this corpus can help provide relevant, human-created instant responses. We distil lessons learned for those developing conversational agents or other AI-infused systems about how to appropriately enlist human-in-the-loop information services to benefit users, task workers and system performance.

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“…Prior research on designing mobile interactions for low-literate users suggests that voice-based interactions are more effective than alternative modalities [55]. Existing approaches typically use either speech recognition, as in the SMART system [41], or IVR systems-as in the Baang and Polly systems [67,86]. IVR systems have been widely studied in the CHI and ICTD communities for engaging low-literate users [46], as in work on agricultural voice forums [61], grievance redressal [52], community media [37,56], and social networks, particularly for visually-impaired users [20,68,84].…”

Section: Voice-based Technologies For Low-literate Usersmentioning

confidence: 99%

“…Future work may thus consider designing computational models of students' digital literacy skill acquisition using system data or assessments and suggest support from family members or other supporters at the right time, such as when students encounter content requiring new interaction modalities (e.g., opening an SMS message). For designers of interactive voice systems (e.g., [52,56,61,[67][68][69]), our findings suggest that, if such systems are to be designed for children, they should be designed to explicitly scaffold technological fluency for IVR.…”

Section: Designing For Digital Literacy Skill Acquisitionmentioning

confidence: 99%

Collective Support and Independent Learning with a Voice-Based Literacy Technology in Rural Communities

Madaio

Yarzebinski

Kamath

et al. 2020

Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems

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Access to literacy is critical to children's futures, but formal education may be insufficient for fostering early literacy, especially in low-resource contexts. Educational technologies used at home may be able to help, but it is unclear whether or how children (and families) will use such technologies at home in rural communities, particularly in low-literate families. In this paper, we investigate these questions with a voice-based literacy technology deployed with families in 8 rural communities in Côte d'Ivoire for 4 months. We use interviews and observations with 37 families to investigate motivations, methods, and barriers for rural families' engagement with a literacy technology accessible via feature phones. We contribute insights into how families view digital literacy as a learning goal, leverage networks of supporters, and over time, transition from explicit to implicit support for children's learning.

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Viral Spread via Entertainment and Voice-Messaging Among Telephone Users in India

Cited by 18 publications

References 22 publications

StreetWise

StreetWise

An Honest Conversation: Transparently Combining Machine and Human Speech Assistance in Public Spaces

Collective Support and Independent Learning with a Voice-Based Literacy Technology in Rural Communities

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