How Do Illiterate People Interact with an Intelligent Voice Assistant?

References

• Abdolrahmani, A., Kuber, R., & Branham, S. M. (2018). “Siri talks at you”: An empirical investigation of voice-activated personal assistant (vapa) usage by individuals who are blind [Paper presentation]. Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility, Association for Computing Machinery, New York, NY, USA, pp. 249–258.
   Google Scholar
• Almeida, V., Furtado, E. S., & Furtado, V. (2020). Personal digital assistants: The need for governance. IEEE Internet Computing, 24(6), 59–64. https://doi.org/10.1109/MIC.2020.3009897
   Web of Science ®Google Scholar
• Amershi, S., Weld, D., Vorvoreanu, M., Fourney, A., Nushi, B., Collisson, P., Suh, J., Iqbal, S., Bennett, P. N., Inkpen, K., Teevan, J., Kikin-Gil, R., & Horvitz, E. (2019). Guidelines for human-AI interaction [Paper presentation]. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 1–13.
   Google Scholar
• Aragão, M. (2015). Atlas Lingüístico do Estado do Ceará (ALECE) (p. 137–148). https://doi.org/10.4000/geolinguistique.642
   Google Scholar
• Ashktorab, Z., Jain, M., Liao, Q. V., & Weisz, J. D. (2019). Resilient chatbots: Repair strategy preferences for conversational breakdowns [Paper presentation]. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 1–12.
   Google Scholar
• Azevedo, R. F., Morrow, D., Graumlich, J., Willemsen-Dunlap, A., Hasegawa-Johnson, M., Huang, T. S., Gu, K., Bhat, S., Sakakini, T., Sadauskas, V., & D. J. Halpin. (2018). Using conversational agents to explain medication instructions to older adults. In AMIA Annual Symposium Proceedings (p. 185–194). American Medical Informatics Association.
   Google Scholar
• Baee, S., Rucker, M., Baglione, A., Ameko, M. K., & Barnes, L. (2020). A framework for addressing the risks and opportunities in al-supported virtual health coaches [Paper presentation]. Proceedings of the 14th EAI International Conference on Pervasive Computing Technologies for Healthcare, Atlanta, GA, USA, pp. 251–254.
   Google Scholar
• Bagno, M. (1999). Preconceito lingüístico: o que é, como se faz. Edições Loyola.
   Google Scholar
• Ballati, F., Corno, F., & De Russis, L. (2018). Assessing virtual assistant capabilities with italian dysarthric speech [Paper presentation]. Proceedings of the 20th International ACM SIGACCESS Conference on Computers and Accessibility, Association for Computing Machinery, New York, NY, USA, pp. 93–101.
   Google Scholar
• Belini, R. G. de C., & Sousa, M. M. F. de. (2014). A variação linguística no livro didático: um olhar sob a perspectiva sociolinguística. (Con)textos Linguísticos, Vitória, 8(10), 211–230.
   Google Scholar
• Berkman, N. D., Sheridan, S. L., Donahue, K. E., Halpern, D. J., & Crotty, K. (2011). Low health literacy and health outcomes: An updated systematic review. Annals of Internal Medicine, 155(2), 97–107. https://doi.org/10.7326/0003-4819-155-2-201107190-00005
   PubMed Web of Science ®Google Scholar
• Blake, E., & Tucker, W. (2006). User interfaces for communication bridges across the digital divide. AI & Society, 20(2), 232–242. https://doi.org/10.1007/s00146-005-0018-1.4
   Google Scholar
• Brandão, S. F. (2015). Pour une approche géo-sociolinguistique de la réalité linguistique brésilienne. Géolinguistique, 15, 191–214. https://doi.org/10.4000/geolinguistique.666
   Google Scholar
• Buhalis, D., & Moldavska, I. (2022). Voice assistants in hospitality: Using artificial intelligence for customer service. Journal of Hospitality and Tourism Technology, 13(3), 386–403. https://doi.org/10.1108/JHTT-03-2021-0104
   Web of Science ®Google Scholar
• Cardoso, S. A. (2010). Geolinguística: tradição e modernidade (1st ed., 200p.). Ed. Contexto. Parabola.
   Google Scholar
• Chaudhuri, B., Kendall, L., Bhalla, A. (2020). Beyond IVR: Exploring voice user interfaces for digital inclusion among urban smartphone users in India. In J. F. George, S. Paul, R. De', E. Karahanna, S. Sarker, & G. Oestreicher-Singer (Eds.), Proceedings of the 41st International Conference on Information Systems, ICIS 2020, Making Digital Inclusive: Blending the Locak and the Global, Hyderabad, India, December 13–16. Association for Information Systems.
   Google Scholar
• Clark, L., Doyle, P., Garaialde, D., Gilmartin, E., Schlögl, S., Edlund, J., Aylett, M., Cabral, J., Munteanu, C., Edwards, J., & R Cowan, B. (2019). The state of speech in HCI: Trends, themes and challenges. Interacting with Computers, 31(4), 349–371. https://doi.org/10.1093/iwc/iwz016
   Web of Science ®Google Scholar
• Cowan, B. R., Pantidi, N., Coyle, D., Morrissey, K., Clarke, P., Al-Shehri, S., Earley, D., & Bandeira, N. (2017). ”What can I help you with?”: Infrequent users’ experiences of intelligent personal assistants [Paper presentation]. Proceedings of the 19th International Conference on Human-Computer Interaction with Mobile Devices and Services, in Association for Computing Machinery, New York, NY, USA.
   Google Scholar
• Dambanemuya, H. K., Diakopoulos, N. (2020). “Alexa, what is going on with the impeachment?” Evaluating smart speakers for news quality. In Proceedings of the Computation and Journalism Symposium, Boston, MA, pp. 1–4.
   Google Scholar
• Elbert, S. P., & Ots, P. (2018). Reading or listening to a gain-or loss-framed health message: Effects of message framing and communication mode in the context of fruit and vegetable intake. Journal of Health Communication, 23(6), 573–580. https://doi.org/10.1080/10810730.2018.1493059
   PubMed Web of Science ®Google Scholar
• de Geografia e Estatística, I. I. B. (2019). Pesquisa nacional por amostra de domicílios contínua anual. https://www.ibge.gov.br/estatisticas/sociais/trabalho/17270-pnad-continua.html (accessed April 16, 2021).
   Google Scholar
• Floccia, C., Goslin, J., Girard, F., & Konopczynski, G. (2006). Does a regional accent perturb speech processing? Journal of Experimental Psychology, 32(5), 1276–1293. https://doi.org/10.1037/0096-1523.32.5.1276
   Google Scholar
• Google. (2020a). Associe a sua voz ao seu dispositivo com o assistente google através do voice match @ONLINE. https://support.google.com/assistant/answer/9071681?co=GENIE.Platform%3DAndroid&hl=pt. (accessed June 6 2020).
   Google Scholar
• Google. (2020b). Google assistant, your own personal google @ONLINE. https://assistant.google.com (accessed November 21, 2020).
   Google Scholar
• Google. (2020c). Speech to text google @ONLINE. https://cloud.google.com/speech-to-text (accessed June 6 2020).
   Google Scholar
• Hone, K. S., & Graham, R. (2000). Towards a tool for the subjective assessment of speech system interfaces (sassi). Natural Language Engineering, 6(3&4), 287–303. https://doi.org/10.1017/S1351324900002497
   Google Scholar
• INAF. (2009). Inaf brasil – indicador de alfabetismo funcional – 2009. http://www.ibope.com.br/ipm/relatorios/relatorio-inaf-2009.pdf. (accessed May 3, 2020).
   Google Scholar
• Kang, D., Gangal, V., & Hovy, E. (2019). (Male, Bachelor) and (Female, Ph.D) have different connotations: Parallelly annotated stylistic language dataset with multiple personas. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP). Association for Computational Linguistics. https://doi.org/10.18653/v1/D19-1179
   Google Scholar
• Karusala, N., Vishwanath, A., Vashistha, A., Kumar, S., Kumar, N. (2018). Only if you use English you will get to more things: Using smartphones to navigate multilingualism. Proceedings of CHI 2018, Montreal QC, Canada, pp. 1–14.
   Google Scholar
• Kendall, L., Chaudhuri, B., & Bhalla, A. (2020). Understanding technology as situated practice: Everyday use of voice user interfaces among diverse groups of users in urban India. Information Systems Frontiers, 22(3), 585–605. https://doi.org/10.1007/s10796-020-10015-6
   Web of Science ®Google Scholar
• Kiseleva, J., Williams, K., Jiang, J., Hassan Awadallah, A., Crook, A. C., Zitouni, I., & Anastasakos, T. (2016). Understanding user satisfaction with intelligent assistants [Paper presentation]. Proceedings of the 2016 ACM on Conference on Human Information Interaction and Retrieval, Association for Computing Machinery, New York, NY, USA, pp. 121–130.
   Google Scholar
• Koenecke, A., Nam, A., Lake, E., Nudell, J., Quartey, M., Mengesha, Z., Toups, C., Rickford, J. R., Jurafsky, D., & Goel, S. (2020). Racial disparities in automated speech recognition. Proceedings of the National Academy of Sciences of the United States of America, 117(14), 7684–7689. https://doi.org/10.1073/pnas.1915768117
   PubMed Web of Science ®Google Scholar
• Labov, W. (1973). Sociolinguistic patterns (vol. 4). University of Pennsylvania Press.
   Google Scholar
• Larsen, H. H., Scheel, A. N., Bogers, T., & Larsen, B. (2020). Hands-free but not eyes-free: A usability evaluation of Siri while driving [Paper presentation]. Proceedings of the 2020 Conference on Human Information Interaction and Retrieval, Association for Computing Machinery, New York, NY, USA, pp. 63–72.
   Google Scholar
• Lavado, T. (2019). Em 10 anos no brasil, android foi de 2 smartphones para sistema operacional dominante do mercado. https://glo.bo/2RulUxb (accessed January 27, 2020).
   Google Scholar
• Leite, M. Q. (2008). Português culto e popular: entrelaçamentos. In I SIMELP - Simpósio Mundial de Estudos de Língua Portuguesa, 2008, São Paulo. A língua portuguesa no mundo (v. 1). Artes Gráficas FFLCH.
   Google Scholar
• Lima, L., Furtado, V., Furtado, E., & Almeida, V. (2019). Empirical analysis of bias in voice-based personal assistants [Paper presentation]. Companion Proceedings of the 2019 World Wide Web Conference, Association for Computing Machinery, New York, NY, USA. pp. 533–538.
   Google Scholar
• Lima, L., Furtado, V., Furtado, E. S., Almeida, V., & Silva, T. (2019). Discrimination analysis of intelligent voice assistants [Paper presentation]. Proceedings of the 18th Brazilian Symposium on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA.
   Google Scholar
• Lisetti, C., Amini, R., Yasavur, U., & Rishe, N. (2013). I can help you change! An empathic virtual agent delivers behavior change health interventions. ACM Transactions on Management Information Systems, 4(4), 1–28. https://doi.org/10.1145/2544103
   Google Scholar
• Livescu, K. (2008). Phonological models in automatic speech recognition: Invited talk [Paper presentation]. Proceedings of the Tenth Meeting of ACL Special Interest Group on Computational Morphology and Phonology, pp. 1–1. Association for Computational Linguistics.
   Google Scholar
• Mattos e Silva, R. V. (2002). Para a história do português culto e popular brasileiro: sugestões para uma pauta de pesquisa. Para a história do português brasileiro, 3, 443–464. https://doi.org/10.15304/elg.7.2314
   Google Scholar
• McTear, M., Callejas, Z., & Griol, D. (2016). Introducing the conversational interface (pp. 1–7). Springer International Publishing.
   Google Scholar
• Medhi, I., Prasad, A., & Toyama, K. (2007). Optimal audio-visual representations for illiterate users of computers [Paper presentation]. Proceedings of the 16th International Conference on World Wide Web, Association for Computing Machinery, New York, NY, USA, p. 873–882.
   Google Scholar
• Metz, C. (2020). There is a racial divide in speech-recognition systems, researchers say. The New York Times.
   Google Scholar
• Monte, A. (2019). A influência da escolaridade e do sexo/gênero no uso variável da concordância verbal de terceira pessoa do plural. Revista Diálogos, 7, 89–104. https://periodicoscientificos.ufmt.br/ojs/index.php/revdia/article/view/7493
   Google Scholar
• Moses, O. O., & Olawole, A. I. (2013). An experimental comparison of speech and DTMF for voicexml-based expert systems. African Journal of Computing & ICT, 6, 1–14.
   Google Scholar
• Myers, C., Furqan, A., Nebolsky, J., Caro, K., & Zhu, J. (2018). Patterns for how users overcome obstacles in voice user interfaces [Paper presentation]. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 1–7.
   Google Scholar
• Myers, C. M., Furqan, A., & Zhu, J. (2019a). The impact of user characteristics and preferences on performance with an unfamiliar voice user interface [Paper presentation]. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland, UK, pp. 1–9.
   Google Scholar
• Myers, C. M., Furqan, A., & Zhu, J. (2019b). The impact of user characteristics and preferences on performance with an unfamiliar voice user interface [Paper presentation]. CHI ’19: CHI Conference on Human Factors in Computing Systems, Glasgow, Scotland, UK, p. 1–9.
   Google Scholar
• Nielsen, J. (1994). Usability engineering. Morgan Kaufmann.
   Google Scholar
• Patel, N., Chittamuru, D., Jain, A., Dave, P., & Parikh, T. S. (2010). Avaaj otalo: A field study of an interactive voice forum for small farmers in rural India [Paper presentation]. Proceedings of the 28th International Conference on Human Factors in Computing Systems – CHI 10, Atlanta, GA, USA, pp. 733–742.
   Google Scholar
• Porcheron, M., Fischer, J. E., Reeves, S., & Sharples, S. (2018). Voice interfaces in everyday life [Paper presentation]. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 1–12.
   Google Scholar
• Pradhan, A., Lazar, A., & Findlater, L. (2020). Use of intelligent voice assistants by older adults with low technology use. ACM Transactions on Computer-Human Interaction, 27(4), 1–27. https://doi.org/10.1145/3373759
   Web of Science ®Google Scholar
• Prates, R. O., de Souza, C. S., & Barbosa, S. D. J. (2000). Methods and tools: A method for evaluating the communicability of user interfaces. Interactions, 7(1), 31–38. https://doi.org/10.1145/328595.328608
   Google Scholar
• Pyae, A., & Joelsson, T. N. (2018). Investigating the usability and user experiences of voice user interface: A case of google home smart speaker [Paper presentation]. Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct, Association for Computing Machinery, New York, NY, USA, pp. 127–131.
   Google Scholar
• Pyae, A., & Scifleet, P. (2018). Investigating differences between native English and non-native English speakers in interacting with a voice user interface: A case of google home [Paper presentation]. Proceedings of the 30th Australian Conference on Computer-Human Interaction, Association for Computing Machinery, New York, NY, USA, pp. 548–553.
   Google Scholar
• Rastogi, A., Zang, X., Sunkara, S., Gupta, R., Khaitan, P. (2020). Towards scalable multi-domain conversational agents: The schema-guided dialogue dataset. In The Thirty-Fourth AAAI Conference on Artificial Intelligence (AAAI-20) will be held February 7–12, 2020 at the Hilton New York Midtown, New York, New York, USA, pp. 8689–8696.
   Google Scholar
• Ratzan, S. C., & Parker, R. M. (2006). Health literacy–identification and response. Journal of Health Communication, 11, 713–715. https://doi.org/10.1080/10810730601031090
   Google Scholar
• Raza, A. A., Ul Haq, F., Tariq, Z., Pervaiz, M., Razaq, S., Saif, U., & Rosenfeld, R. (2013). Job opportunities through entertainment: Virally spread speech-based services for low-literate users [Paper presentation]. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 2803–2812.
   Google Scholar
• Rodrigues, Â. C. S. (1988). A concordância verbal do português popular em são paulo. Linha D'Água, 0(5), 92–94. https://doi.org/10.11606/issn.2236-4242.v0i5p92-94
   Google Scholar
• Sayago, S., Neves, B. B., & Cowan, B. R. (2019). Voice assistants and older people: Some open issues [Paper presentation]. Proceedings of the 1st International Conference on Conversational User Interfaces, Association for Computing Machinery, New York, NY, USA.
   Google Scholar
• SEDUC. (2020). Educação de jovens e adultos { eja. https://www.seduc.ce.gov.br/educacao-de-jovens-e-adultos-eja/ (accessed January 27, 2020).
   Google Scholar
• Soares, M., Mesquita, L., Oliveira, F., & Rodrigues, L. (2019). Ana: A natural language system with multimodal interaction for people who have tetraplegia. In M. Antona, & C. Stephanidis (Eds.), Universal access in human-computer interaction, multimodality and assistive environments (pp. 353–362). Springer International Publishing.
   Google Scholar
• Tarallo, F. (1985). A pesquisa sociolingüística. Ática.
   Google Scholar
• Teixeira, M. S., Maran, V., Dragoni, M. (2021). The interplay of a conversational ontology and AI planning for health dialogue management. SAC ’21: Proceedings of the 36th Annual ACM Symposium on Applied Computing, pp. 611–619. Association for Computing Machinery. https://doi.org/10.1145/3412841.3441942
   Google Scholar
• UNESCO. (2017). Literacy rates continue to rise from one generation to the next. UNESCO Institute for Statistics (UIS). https://bit.ly/3tliooz Access in 06/05/2021.
   Google Scholar
• Venkatesh, V., & Davis, F. D. (2000). A theoretical extension of the technology acceptance model: Four longitudinal field studies. Management Science, 46(2), 186–204., https://doi.org/10.1287/mnsc.46.2.186.11926, arXiv:https://doi.org/10.1287/mnsc.46.2.186.11926
   Web of Science ®Google Scholar
• Vtyurina, A., & Fourney, A. (2018). Exploring the role of conversational cues in guided task support with virtual assistants [Paper presentation]. Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems, Association for Computing Machinery, New York, NY, USA, pp. 1–7.
   Google Scholar
• Walker, M. A., Litman, D. J., Kamm, C. A., & Abella, A. (1997). Paradise: A framework for evaluating spoken dialogue agents. arXiv:cmp-lg/9704004. https://doi.org/10.48550/arXiv.cmp-lg/9704004
   Google Scholar
• Wang, Y.-Y., Acero, A., & Chelba, C. (2003). Is word error rate a good indicator for spoken language understanding accuracy [Paper presentation]. 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, St. Thomas, US Virgin Islands, pp. 577–582.
   Google Scholar
• Weinreich, U., Labov, W., & Herzog, M. (1968). Empirical foundations for a theory of language change (vol. 58). University of Texas Press Austin.
   Google Scholar
• Wiese, R. (1984). Language production in foreign and native languages: Same or different?. In H. W. Dechert, D. Möhle, & M. Raupach (Eds.), Second language production (pp. 11–25). Gunter Narr Verlag.
   Google Scholar
• Wu, Y., Edwards, J., Cooney, O., Bleakley, A., Doyle, P. R., Clark, L., Rough, D., & Cowan, B. R. (2020). Mental workload and language production in non-native speaker IPA interaction [Paper presentation]. Proceedings of the 2nd Conference on Conversational User Interfaces, Association for Computing Machinery, New York, NY, USA.
   Google Scholar
• Zheng, Y., Sproat, R., Gu, L., Shafran, I., Zhou, H., Su, Y., Jurafsky, D., Starr, R., & Yoon, S. Y. (2005). Accent detection and speech recognition for Shanghai-accented Mandarin. Ninth European Conference on Speech Communication and Technology, Lisbon, Portugal.
   Google Scholar
• Zilio, L., Paraguassu, L. B., Hercules, L. A. L., Ponomarenko, G., Berwanger, L., Finatto, M. J. B. (2020). A lexical simplification tool for promoting health literacy. Proceedings of the 1st Workshop on Tools and Resources to Empower People with REAding DIfficulties (READI), Marseille, France, pp. 70–76.
   Google Scholar