skip to main content
research-article
Open Access

One Voice Fits All?: Social Implications and Research Challenges of Designing Voices for Smart Devices

Published:07 November 2019Publication History
Skip Abstract Section

Abstract

When a smart device talks, what should its voice sound like? Voice-enabled devices are becoming a ubiquitous presence in our everyday lives. Simultaneously, speech synthesis technology is rapidly improving, making it possible to generate increasingly varied and realistic computerized voices. Despite the flexibility and richness of expression that technology now affords, today's most common voice assistants often have female-sounding, polite, and playful voices by default. In this paper, we examine the social consequences of voice design, and introduce a simple research framework for understanding how voice affects how we perceive and interact with smart devices. Based on the foundational paradigm of computers as social actors, and informed by research in human-robot interaction, this framework demonstrates how voice design depends on a complex interplay between characteristics of the user, device, and context. Through this framework, we propose a set of guiding questions to inform future research in the space of voice design for smart devices.

References

  1. Nalini Ambady and Robert Rosenthal. 1993. Half a minute: Predicting teacher evaluations from thin slices of nonverbal behavior and physical attractiveness. Journal of personality and social psychology , Vol. 64, 3 (1993), 431.Google ScholarGoogle ScholarCross RefCross Ref
  2. Tawfiq Ammari, Jofish Kaye, Janice Y. Tsai, and Frank Bentley. 2019. Music, Search, and IoT: How People (Really) Use Voice Assistants . ACM Trans. Comput.-Hum. Interact. , Vol. 26, 3 (April 2019), 17:1--17:28. https://doi.org/10.1145/3311956Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Guozhen An, Sarah Ita Levitan, Julia Hirschberg, and Rivka Levitan. 2018. Deep Personality Recognition for Deception Detection. In Proc. Interspeech 2018 . 421--425. https://doi.org/10.21437/Interspeech.2018--2269Google ScholarGoogle ScholarCross RefCross Ref
  4. Sean Andrist, Micheline Ziadee, Halim Boukaram, Bilge Mutlu, and Majd Sakr. 2015. Effects of Culture on the Credibility of Robot Speech: A Comparison between English and Arabic. In Proceedings of the Tenth Annual ACM/IEEE International Conference on Human-Robot Interaction - HRI '15 . ACM Press, Portland, Oregon, USA, 157--164. https://doi.org/10.1145/2696454.2696464Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Matthew P. Aylett, Benjamin R. Cowan, and Leigh Clark. 2019. Siri, Echo and Performance: You Have to Suffer Darling. In Extended Abstracts of the 2019 CHI Conference on Human Factors in Computing Systems (CHI EA '19). ACM, New York, NY, USA, alt08:1--alt08:10. https://doi.org/10.1145/3290607.3310422 event-place: Glasgow, Scotland Uk.Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Christoph Bartneck, Kumar Yogeeswaran, Qi Min Ser, Graeme Woodward, Robert Sparrow, Siheng Wang, and Friederike Eyssel. 2018. Robots And Racism. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI '18). ACM, New York, NY, USA, 196--204. https://doi.org/10.1145/3171221.3171260 event-place: Chicago, IL, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. Erin Beneteau, Olivia K. Richards, Mingrui Zhang, Julie A. Kientz, Jason Yip, and Alexis Hiniker. 2019. Communication Breakdowns Between Families and Alexa. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI '19). ACM, New York, NY, USA, 243:1--243:13. https://doi.org/10.1145/3290605.3300473 event-place: Glasgow, Scotland Uk.Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Meera M. Blattner, Denise A. Sumikawa, and Robert M. Greenberg. 1989. Earcons and Icons: Their Structure and Common Design Principles (Abstract Only). SIGCHI Bull. , Vol. 21, 1 (Aug. 1989), 123--124. https://doi.org/10.1145/67880.1046599Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Dieter Bohn. 2019. Amazon says 100 million Alexa devices have been sold. https://www.theverge.com/2019/1/4/18168565/amazon-alexa-devices-how-many-sold-number-100-million-dave-limpGoogle ScholarGoogle Scholar
  10. Lera Boroditsky, Lauren A Schmidt, and Webb Phillips. 2003. Sex, syntax, and semantics. Language in mind: Advances in the study of language and thought (2003), 61--79.Google ScholarGoogle Scholar
  11. Robin N. Brewer, Leah Findlater, Joseph 'Jofish' Kaye, Walter Lasecki, Cosmin Munteanu, and Astrid Weber. 2018. Accessible Voice Interfaces. In Companion of the 2018 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '18). ACM, New York, NY, USA, 441--446. https://doi.org/10.1145/3272973.3273006 event-place: Jersey City, NJ, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. Minsuk Chang, Anh Truong, Oliver Wang, Maneesh Agrawala, and Juho Kim. 2019. How to Design Voice Based Navigation for How-To Videos . Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19 (2019), 11.Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Rebecca Cherng-Shiow Chang, Hsi-Peng Lu, and Peishan Yang. 2018. Stereotypes or golden rules? Exploring likable voice traits of social robots as active aging companions for tech-savvy baby boomers in Taiwan . Computers in Human Behavior , Vol. 84 (July 2018), 194--210. https://doi.org/10.1016/j.chb.2018.02.025Google ScholarGoogle Scholar
  14. Brian X. Chen. 2019. Devices That Will Invade Your Life in 2019 (and What's Overhyped) .Google ScholarGoogle Scholar
  15. Leigh Clark, Phillip Doyle, Diego Garaialde, Emer Gilmartin, Stephan Schlögl, Jens Edlund, Matthew Aylett, João Cabral, Cosmin Munteanu, and Benjamin Cowan. 2018. The State of Speech in HCI: Trends, Themes and Challenges . arXiv preprint arXiv:1810.06828 (2018).Google ScholarGoogle Scholar
  16. Leigh Clark, Abdulmalik Ofemile, Svenja Adolphs, and Tom Rodden. 2016. A Multimodal Approach to Assessing User Experiences with Agent Helpers . ACM Trans. Interact. Intell. Syst. , Vol. 6, 4 (Nov. 2016), 29:1--29:31. https://doi.org/10.1145/2983926Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Phil Cohen, Adam Cheyer, Eric Horvitz, Rana El Kaliouby, and Steve Whittaker. 2016. On the Future of Personal Assistants . Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems - CHI EA '16 (2016), 1032--1037. https://doi.org/10.1145/2851581.2886425Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Dan Kedmey. 2015. Microsoft's Cortana Gets a Crash Course in Cultural Sensitivity textbar Time . Time Magazine (July 2015). http://time.com/3960670/windows-10-cortana/Google ScholarGoogle Scholar
  19. Andreea Danielescu and Gwen Christian. 2018. A Bot is Not a Polyglot . Extended Abstracts of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 (2018), 1--9. https://doi.org/10.1145/3170427.3174366Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. Guy Deutscher. 2010. Through the language glass: Why the world looks different in other languages .Metropolitan Books.Google ScholarGoogle Scholar
  21. W. Keith Edwards and Elizabeth D. Mynatt. 1994. An Architecture for Transforming Graphical Interfaces. In Proceedings of the 7th Annual ACM Symposium on User Interface Software and Technology (UIST '94). ACM, New York, NY, USA, 39--47. https://doi.org/10.1145/192426.192443 event-place: Marina del Rey, California, USA.Google ScholarGoogle Scholar
  22. Kerstin Fischer, Katrin S Lohan, and Kilian Foth. 2012. Levels of embodiment: Linguistic analyses of factors influencing HRI. In Proceedings of the seventh annual ACM/IEEE international conference on Human-Robot Interaction. ACM, 463--470.Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. BJ Fogg, Gregory Cuellar, and David Danielson. 2019. Motivating, influencing, and persuading users: An introduction to captology. (2019).Google ScholarGoogle Scholar
  24. William W Gaver. 1989. The SonicFinder: An interface that uses auditory icons. Human--Computer Interaction , Vol. 4, 1 (1989), 67--94.Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. Erving Goffman. 1978. The presentation of self in everyday life .Harmondsworth London.Google ScholarGoogle Scholar
  26. Rajat Hebbar, Krishna Somandepalli, and Shrikanth Narayanan. 2018. Improving Gender Identification in Movie Audio Using Cross-Domain Data. In Proc. Interspeech 2018. 282--286. https://doi.org/10.21437/Interspeech.2018--1462Google ScholarGoogle ScholarCross RefCross Ref
  27. Laura Hoffmann, Nikolai Bock, and Astrid M. Rosenthal v.d. Pütten. 2018. The Peculiarities of Robot Embodiment (EmCorp-Scale): Development, Validation and Initial Test of the Embodiment and Corporeality of Artificial Agents Scale. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction (HRI '18). ACM, New York, NY, USA, 370--378. https://doi.org/10.1145/3171221.3171242 event-place: Chicago, IL, USA.Google ScholarGoogle Scholar
  28. Miwa Ikemiya and Daniela K. Rosner. 2014. Broken Probes: Toward the Design of Worn Media . Personal Ubiquitous Comput. , Vol. 18, 3 (March 2014), 671--683. https://doi.org/10.1007/s00779-013-0690-yGoogle ScholarGoogle ScholarDigital LibraryDigital Library
  29. James Vincent. 2018. Google launches more realistic text-to-speech service powered by DeepMind's AI - The Verge . https://www.theverge.com/2018/3/27/17167200/google-ai-speech-tts-cloud-deepmind-wavenetGoogle ScholarGoogle Scholar
  30. Eun Hwa Jung, T. Franklin Waddell, and S. Shyam Sundar. 2016. Feminizing Robots: User Responses to Gender Cues on Robot Body and Screen. In Proceedings of the 2016 CHI Conference Extended Abstracts on Human Factors in Computing Systems - CHI EA '16. ACM Press, Santa Clara, California, USA, 3107--3113. https://doi.org/10.1145/2851581.2892428Google ScholarGoogle ScholarDigital LibraryDigital Library
  31. Alisa Kalegina, Grace Schroeder, Aidan Allchin, Keara Berlin, and Maya Cakmak. 2018. Characterizing the Design Space of Rendered Robot Faces. In Proceedings of the 2018 ACM/IEEE International Conference on Human-Robot Interaction - HRI '18. ACM Press, Chicago, IL, USA, 96--104. https://doi.org/10.1145/3171221.3171286Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Os Keyes. 2018. The Misgendering Machines: Trans/HCI Implications of Automatic Gender Recognition . Proc. ACM Hum.-Comput. Interact. , Vol. 2, CSCW (Nov. 2018), 88:1--88:22. https://doi.org/10.1145/3274357Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. Sara Kiesler, Aaron Powers, Susan R Fussell, and Cristen Torrey. 2008. Anthropomorphic interactions with a robot and robot--like agent. Social Cognition , Vol. 26, 2 (2008), 169--181.Google ScholarGoogle ScholarCross RefCross Ref
  34. Sei Jin Ko, Charles M. Judd, and Irene V. Blair. 2006. What the Voice Reveals: Within- and Between-Category Stereotyping on the Basis of Voice . Personality and Social Psychology Bulletin , Vol. 32, 6 (2006), 806--819. https://doi.org/10.1177/0146167206286627Google ScholarGoogle ScholarCross RefCross Ref
  35. Rafal Kocielnik, Daniel Avrahami, Jennifer Marlow, Di Lu, and Gary Hsieh. 2018. Designing for Workplace Reflection: A Chat and Voice-Based Conversational Agent . Proceedings of the 2018 Designing Interactive Systems Conference (2018), 881--894. https://doi.org/10.1145/3196709.3196784Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Josephine Lau, Benjamin Zimmerman, and Florian Schaub. 2018. Alexa, Are You Listening?: Privacy Perceptions, Concerns and Privacy-seeking Behaviors with Smart Speakers . Proc. ACM Hum.-Comput. Interact. , Vol. 2, CSCW (Nov. 2018), 102:1--102:31. https://doi.org/10.1145/3274371Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. Lauren Goode. 2018. How Google's Eerie Robot Phone Calls Hint at AI's Future . Wired (May 2018). https://www.wired.com/story/google-duplex-phone-calls-ai-future/Google ScholarGoogle Scholar
  38. Kwan Min Lee, Wei Peng, Seung-A Jin, and Chang Yan. 2006. Can Robots Manifest Personality?: An Empirical Test of Personality Recognition, Social Responses, and Social Presence in Human--Robot Interaction . Journal of Communication , Vol. 56, 4 (2006), 754--772. https://doi.org/10.1111/j.1460--2466.2006.00318.xGoogle ScholarGoogle ScholarCross RefCross Ref
  39. M. K. Lee, S. Kiesler, J. Forlizzi, S. Srinivasa, and P. Rybski. 2010. Gracefully mitigating breakdowns in robotic services. In 2010 5th ACM/IEEE International Conference on Human-Robot Interaction (HRI) . 203--210. https://doi.org/10.1109/HRI.2010.5453195Google ScholarGoogle Scholar
  40. Lily Hay Newman. 2014. This Social Robot Is Adorable. But Will Families Actually Want One? Slate (July 2014). https://slate.com/technology/2014/07/social-robotics-expert-cynthia-breazeal-debuts-jibo-a-family-robot.htmlGoogle ScholarGoogle Scholar
  41. Nichola Lubold, Erin Walker, and Heather Pon-Barry. 2016. Effects of voice-adaptation and social dialogue on perceptions of a robotic learning companion. In 2016 11th ACM/IEEE International Conference on Human-Robot Interaction (HRI). IEEE, 255--262.Google ScholarGoogle ScholarCross RefCross Ref
  42. Nichola Lubold, Erin Walker, Heather Pon-Barry, and Amy Ogan. 2018. Automated pitch convergence improves learning in a social, teachable robot for middle school mathematics. In International Conference on Artificial Intelligence in Education. Springer, 282--296.Google ScholarGoogle ScholarCross RefCross Ref
  43. Ewa Luger and Abigail Sellen. 2016. "Like Having a Really Bad PA": The Gulf between User Expectation and Experience of Conversational Agents . Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems - CHI '16 (2016), 5286--5297. https://doi.org/10.1145/2858036.2858288Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Nikolas Martelaro and Wendy Ju. 2017. WoZ Way: Enabling Real-time Remote Interaction Prototyping & Observation in On-road Vehicles. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing - CSCW '17. ACM Press, Portland, Oregon, USA, 169--182. https://doi.org/10.1145/2998181.2998293Google ScholarGoogle Scholar
  45. Matt Simon. 2019. The Genderless Digital Voice the World Needs Right Now . https://www.wired.com/story/the-genderless-digital-voice-the-world-needs-right-now/Google ScholarGoogle Scholar
  46. Phil McAleer, Alexander Todorov, and Pascal Belin. 2014. How Do You Say 'Hello'? Personality Impressions from Brief Novel Voices . PLoS ONE , Vol. 9, 3 (March 2014), e90779. https://doi.org/10.1371/journal.pone.0090779Google ScholarGoogle ScholarCross RefCross Ref
  47. C. McGinn and I. Torre. 2019. Can you Tell the Robot by the Voice? An Exploratory Study on the Role of Voice in the Perception of Robots. In 2019 14th ACM/IEEE International Conference on Human-Robot Interaction (HRI) . 211--221. https://doi.org/10.1109/HRI.2019.8673305Google ScholarGoogle Scholar
  48. Moira McGregor and John C. Tang. 2017. More to Meetings: Challenges in Using Speech-Based Technology to Support Meetings. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17). ACM, New York, NY, USA, 2208--2220. https://doi.org/10.1145/2998181.2998335 event-place: Portland, Oregon, USA.Google ScholarGoogle Scholar
  49. Michal Luria, Samantha Reig, Xiang Zhi Tan, Aaron Steinfeld, Jodi Forlizzi, and John Zimmerman. [n. d.]. Re-Embodiment and Co-Embodiment: Exploration of Social Presence for Robots and Conversational Agents. In Proceedings of the 2018 on Designing Interactive Systems Conference 2019 - DIS '19 .Google ScholarGoogle Scholar
  50. Rani Molla. 2018. Voice tech like Alexa and Siri hasn't found its true calling yet: Inside the voice assistant 'revolution'. Recode (2018). https://www.recode.net/2018/11/12/17765390/voice-alexa-siri-assistant-amazon-echo-google-assistantGoogle ScholarGoogle Scholar
  51. Juan Manuel Montero, Juana M Gutierrez-Arriola, Sira Palazuelos, Emilia Enriquez, Santiago Aguilera, and José Manuel Pardo. 1998. Emotional speech synthesis: From speech database to TTS. In Fifth International Conference on Spoken Language Processing.Google ScholarGoogle Scholar
  52. Dylan Moore, Hamish Tennent, Nikolas Martelaro, and Wendy Ju. 2017. Making noise intentional: A study of servo sound perception. In Proceedings of the 2017 ACM/IEEE International Conference on Human-Robot Interaction. ACM, 12--21.Google ScholarGoogle ScholarDigital LibraryDigital Library
  53. Roger K Moore. 2017a. Appropriate Voices for Artefacts: Some Key Insights. In 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots.Google ScholarGoogle Scholar
  54. Roger K. Moore. 2017b. Is Spoken Language All-or-Nothing? Implications for Future Speech-Based Human-Machine Interaction . In Dialogues with Social Robots: Enablements, Analyses, and Evaluation , , Kristiina Jokinen and Graham Wilcock (Eds.). Springer Singapore, Singapore, 281--291. https://doi.org/10.1007/978--981--10--2585--3_22Google ScholarGoogle Scholar
  55. Christine Murad, Cosmin Munteanu, Leigh Clark, and Benjamin R Cowan. 2018. Design Guidelines for Hands-free Speech Interaction. In Proceedings of the 20th International Conference on Human-Computer Interaction with Mobile Devices and Services Adjunct (MobileHCI '18). ACM, New York, NY, USA, 269--276. https://doi.org/10.1145/3236112.3236149Google ScholarGoogle ScholarDigital LibraryDigital Library
  56. Bilge Mutlu, Steven Osman, Jodi Forlizzi, Jessica Hodgins, and Sara Kiesler. 2006. Task Structure and User Attributes as Elements of Human-Robot Interaction Design. In ROMAN 2006 - The 15th IEEE International Symposium on Robot and Human Interactive Communication. IEEE, Univ. of Hertfordshire, Hatfield, UK, 74--79. https://doi.org/10.1109/ROMAN.2006.314397Google ScholarGoogle ScholarCross RefCross Ref
  57. Chelsea Myers, Anushay Furqan, Jessica Nebolsky, Karina Caro, and Jichen Zhu. 2018. Patterns for How Users Overcome Obstacles in Voice User Interfaces. In Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems (CHI '18). ACM, New York, NY, USA, 6:1--6:7. https://doi.org/10.1145/3173574.3173580 event-place: Montreal QC, Canada.Google ScholarGoogle ScholarDigital LibraryDigital Library
  58. Clifford Nass and Scott Brave. 2005. Wired for speech: How voice activates and advances the human-computer relationship. MIT press.Google ScholarGoogle ScholarDigital LibraryDigital Library
  59. Clifford Nass and Kwan Min Lee. 2001. Does computer-synthesized speech manifest personality? Experimental tests of recognition, similarity-attraction, and consistency-attraction. Journal of experimental psychology: applied , Vol. 7, 3 (2001), 171.Google ScholarGoogle ScholarCross RefCross Ref
  60. Clifford Nass, Jonathan Steuer, and Ellen R. Tauber. 1994. Computers Are Social Actors. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI '94). ACM, New York, NY, USA, 72--78. https://doi.org/10.1145/191666.191703 event-place: Boston, Massachusetts, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  61. Kenneth Olmstead. 2017. Nearly half of Americans use digital voice assistants, mostly on their smartphones . Technical Report. Pew Research Center. https://www.pewresearch.org/fact-tank/2017/12/12/nearly-half-of-americans-use-digital-voice-assistants-mostly-on-their-smartphones/Google ScholarGoogle Scholar
  62. Aaron van den Oord, Sander Dieleman, Heiga Zen, Karen Simonyan, Oriol Vinyals, Alex Graves, Nal Kalchbrenner, Andrew Senior, and Koray Kavukcuoglu. 2016. Wavenet: A generative model for raw audio. arXiv preprint arXiv:1609.03499 (2016).Google ScholarGoogle Scholar
  63. Sarah Perez. 2018. Alexa developers get 8 free voices to use in skills, courtesy of Amazon Polly . TechCrunch (May 2018). https://techcrunch.com/2018/05/16/alexa-developers-get-8-free-voices-to-use-in-skills-courtesy-of-amazon-polly/Google ScholarGoogle Scholar
  64. Martha L Picariello, Danna N Greenberg, and David B Pillemer. 1990. Children's sex-related stereotyping of colors. Child Development , Vol. 61, 5 (1990), 1453--1460.Google ScholarGoogle ScholarCross RefCross Ref
  65. Martin Porcheron, Joel E Fischer, Stuart Reeves, and Sarah Sharples. 2018. Voice Interfaces in Everyday Life . Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems - CHI '18 (2018), 1--12. https://doi.org/doi.org/10.1145/3173574.3174214Google ScholarGoogle ScholarDigital LibraryDigital Library
  66. Martin Porcheron, Joel E. Fischer, and Sarah Sharples. 2017. "Do Animals Have Accents?": Talking with Agents in Multi-Party Conversation. In Proceedings of the 2017 ACM Conference on Computer Supported Cooperative Work and Social Computing (CSCW '17). ACM, New York, NY, USA, 207--219. https://doi.org/10.1145/2998181.2998298 event-place: Portland, Oregon, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  67. A Purington, J G Taft, S Sannon, N N Bazarova, and S H Taylor. 2017. "Alexa is my new BFF": Social roles, user satisfaction, and personification of the Amazon Echo . Conference on Human Factors in Computing Systems - Proceedings , Vol. Part F1276 (2017), 2853--2859. https://doi.org/10.1145/3027063.3053246Google ScholarGoogle ScholarDigital LibraryDigital Library
  68. Sara Perez. 2019. Report: Voice assistants in use to triple to 8 billion by 2023 textbar TechCrunch . https://techcrunch.com/2019/02/12/report-voice-assistants-in-use-to-triple-to-8-billion-by-2023/Google ScholarGoogle Scholar
  69. Alex Sciuto, Arnita Saini, Jodi Forlizzi, and Jason I Hong. 2018. "Hey Alexa, What's Up?": A Mixed-Methods Studies of In-Home Conversational Agent Usage . Proceedings of the 2018 on Designing Interactive Systems Conference 2018 - DIS '18 (2018), 857--868. https://doi.org/10.1145/3196709.3196772Google ScholarGoogle ScholarDigital LibraryDigital Library
  70. Selina Jeanne Sutton , Paul Foulkes, David Kirk, and Shaun Lawson. 2019. Voice as a Design Material: Sociophonetic Inspired Design Strategies in Human-Computer Interaction. In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19 . 1--14. https://doi.org/10.1145/3290605.3300833Google ScholarGoogle ScholarDigital LibraryDigital Library
  71. Ben Shneiderman. 2000. The limits of speech recognition. Commun. ACM , Vol. 43, 9 (2000), 63--65. https://doi.org/10.1145/348941.348990Google ScholarGoogle ScholarDigital LibraryDigital Library
  72. Berrak Sisman and Haizhou Li. 2018. Wavelet Analysis of Speaker Dependent and Independent Prosody for Voice Conversion. In Proc. Interspeech 2018 . 52--56. https://doi.org/10.21437/Interspeech.2018--1499Google ScholarGoogle ScholarCross RefCross Ref
  73. Aaron Springer and Henriette Cramer. 2018. 'Play PRBLMS": Identifying and Correcting Less Accessible Content in Voice Interfaces . (2018), 1--13. https://doi.org/10.1145/3173574.3173870Google ScholarGoogle Scholar
  74. Vasant Srinivasan and Leila Takayama. 2016. Help Me Please: Robot Politeness Strategies for Soliciting Help From Humans. In Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems (CHI '16). ACM, New York, NY, USA, 4945--4955. https://doi.org/10.1145/2858036.2858217 event-place: San Jose, California, USA.Google ScholarGoogle ScholarDigital LibraryDigital Library
  75. Chandra Steele. 2018. The Real Reason Voice Assistants Are Female (and Why it Matters). PCMag (2018).Google ScholarGoogle Scholar
  76. Marie Louise Juul Søndergaard and Lone Koefoed Hansen. 2018. Intimate Futures: Staying with the Trouble of Digital Personal Assistants through Design Fiction . Proceedings of the 2018 on Designing Interactive Systems Conference 2018 - DIS '18 (2018), 869--880. https://doi.org/10.1145/3196709.3196766Google ScholarGoogle ScholarDigital LibraryDigital Library
  77. Benedict Tay, Younbo Jung, and Taezoon Park. 2014. When stereotypes meet robots: The double-edge sword of robot gender and personality in human--robot interaction. Computers in Human Behavior , Vol. 38 (Sept. 2014), 75--84. https://doi.org/10.1016/j.chb.2014.05.014Google ScholarGoogle ScholarDigital LibraryDigital Library
  78. Hamish Tennent, Dylan Moore, Malte Jung, and Wendy Ju. 2017. Good vibrations: How consequential sounds affect perception of robotic arms. In 2017 26th IEEE International Symposium on Robot and Human Interactive Communication (RO-MAN). IEEE, 928--935.Google ScholarGoogle ScholarDigital LibraryDigital Library
  79. Cristen Torrey, Susan Fussell, and Sara Kiesler. 2013. How a Robot Should Give Advice. In Proceedings of the 8th ACM/IEEE International Conference on Human-robot Interaction (HRI '13). IEEE Press, Piscataway, NJ, USA, 275--282. http://dl.acm.org/citation.cfm?id=2447556.2447666 event-place: Tokyo, Japan.Google ScholarGoogle ScholarDigital LibraryDigital Library
  80. James Vincent. 2019. Kohler's smart toilet promises a 'fully-immersive experience'. The Verge (2019). https://www.theverge.com/2019/1/6/18170575/kohler-konnect-bathroom-smart-gadgets-numi-intelligent-toilet-ces-2019Google ScholarGoogle Scholar
  81. Mark West, Rebecca Kraut, and Han Ei Chew. 2019. I'd blush if I could: closing gender divides in digital skills through education . Technical Report. UNESCO, EQUALS Skills Coalition. https://unesdoc.unesco.org/ark:/48223/pf0000367416.locale=enGoogle ScholarGoogle Scholar
  82. Mirjam Wester, Cassia Valentini-Botinhao, and Gustav Eje Henter. 2015. Are We Using Enough Listeners? No!-An Empirically-Supported Critique of Interspeech 2014 TTS Evaluations. In Sixteenth Annual Conference of the International Speech Communication Association.Google ScholarGoogle ScholarCross RefCross Ref

Index Terms

  1. One Voice Fits All?: Social Implications and Research Challenges of Designing Voices for Smart Devices

    Recommendations

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    Full Access

    • Published in

      cover image Proceedings of the ACM on Human-Computer Interaction
      Proceedings of the ACM on Human-Computer Interaction  Volume 3, Issue CSCW
      November 2019
      5026 pages
      EISSN:2573-0142
      DOI:10.1145/3371885
      Issue’s Table of Contents

      Copyright © 2019 ACM

      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

      Publisher

      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 7 November 2019
      Published in pacmhci Volume 3, Issue CSCW

      Permissions

      Request permissions about this article.

      Request Permissions

      Check for updates

      Qualifiers

      • research-article

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader