The State of Speech in HCI: Trends, Themes and Challenges
Open accessAbstract
Speech interfaces are growing in popularity. Through a review of 99 research papers this work maps the trends, themes, findings and methods of empirical research on speech interfaces in the field of human–computer interaction (HCI). We find that studies are usability/theory-focused or explore wider system experiences, evaluating Wizard of Oz, prototypes or developed systems. Measuring task and interaction was common, as was using self-report questionnaires to measure concepts like usability and user attitudes. A thematic analysis of the research found that speech HCI work focuses on nine key topics: system speech production, design insight, modality comparison, experiences with interactive voice response systems, assistive technology and accessibility, user speech production, using speech technology for development, peoples’ experiences with intelligent personal assistants and how user memory affects speech interface interaction. From these insights we identify gaps and challenges in speech research, notably taking into account technological advancements, the need to develop theories of speech interface interaction, grow critical mass in this domain, increase design work and expand research from single to multiple user interaction contexts so as to reflect current use contexts. We also highlight the need to improve measure reliability, validity and consistency, in the wild deployment and reduce barriers to building fully functional speech interfaces for research.RESEARCH HIGHLIGHTS: Most papers focused on usability/theory-based or wider system experience research with a focus on Wizard of Oz and developed systems Questionnaires on usability and user attitudes often used but few were reliable or validated Thematic analysis showed nine primary research topics Challenges identified in theoretical approaches and design guidelines, engaging with technological advances, multiple user and in the wild contexts, critical research mass and barriers to building speech interfaces
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VUIs are not conversational in nature.
“As extensively noted in VUI literature, VUIs are not “conversational” in nature [24,25,31,36,45,83].”
From OK Google, Let's Learn: Using Voice User Interfaces for Informal Self-Regulated Learning of Health Topics among Younger and Older Adults (2023) · cites this paper as [24]
Section 2 (p. 2) says current system dialogues are stiff and questions how closely they simulate human conversation, supporting a qualified version of the claim. It does not say VUIs are categorically non-conversational; it also describes spoken dialogue systems as allowing two-way interaction. (LLM, conf=0.88)
Experimental — accuracy not yet measuredResearch in repair strategies has been broadly divided into investigations into system-repair strategies and studies on user-repair strategies.
“Centred on the main dialogue actor in the breakdown-repairing process, research in repair strategies has been broadly divided into two areas: investigations into system-repair strategies and studies on user-repair strategies [10, 16].”
From System and User Strategies to Repair Conversational Breakdowns of Spoken Dialogue Systems: A Scoping Review (2024) · cites this paper as [16]
Section 5.1 (pp. 9–10) divides the speech-HCI papers reviewed into usability/theory-based research and system-experience research, not categories of repair strategies. Searches for repair strategies and breakdown repair found no passage in our copy addressing the claimed system-repair versus user-repair division. (LLM, conf=0.72)
Experimental — accuracy not yet measured
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Self-citationLongitudinal study of people learning to use continuous voice-based cursor control
Harada, S., Wobbrock, J. O., Malkin, J., Bilmes, J., & Landay, J. A. (2009) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1518757 · Cited by 48 · cited 3× · see citing works
“…68 publications on user interactions with speech as either a system output (e.g. Alm, Todman, Elder, & Newell, 1993), user input (e.g. Harada, Wobbrock, Malkin, Bilmes, & Landay, 2009) or in a dialogue context (e.g. Cowan, Branigan, Obregón, Bugis, & Beale, 2015; Porcheron, Fischer, &…”
BackgroundMethodInfluentialAutomated telephone answering systems and aging
Dulude, L. (2002) · Behaviour and Information Technology · doi:10.1080/0144929021000013482 · Cited by 48 · cited 1× · see citing works
“Another paper focused on aging and its effects on IVR experiences (Dulude, 2002).”
BackgroundBegany, G. M., Sa, N., & Yuan, X.-J. (2015) · Interacting with computers · doi:10.1093/iwc/iwv029 · Cited by 48 · cited 2× · see citing works
“Two papers report a negative impact of using speech, with speech reducing ease of system use (Begany et al., 2015), and a user’s sense of agency (Limerick et al., 2015) compared to more traditional input modalities such as keyboard and mouse.”
BackgroundOn the Future of Personal Assistants
Cohen, P., Cheyer, A., Horvitz, E., Kaliouby, R. E., & Whittaker, S. (2016) · CHI Extended Abstracts · doi:10.1145/2851581.2886425 · Cited by 45 · cited 2× · see citing works
“We excluded works in progress and extended abstracts (e.g. Aylett et al., 2015; Cowan et al., 2016), debates or panel discussions (e.g. Cohen et al., 2016) workshop papers (e.g. Munteanu et al., 2017) and magazine articles, for instance those from Communications of the ACM (e.g. Shneiderman, 2000)…”
BackgroundDesigning habitable dialogues for speech-based interaction with computers
Hone, K., & Baber, C. (2001) · Int. J. Hum. Comput. Stud. · doi:10.1006/ijhc.2000.0456 · Cited by 44 · see citing works
Using speech and dialogue for interactive TV navigation
Berglund, A., & Johansson, P. (2004) · Universal Access in the Information Society · doi:10.1007/s10209-004-0106-x · Cited by 42 · see citing works
Voice typing: a new speech interaction model for dictation on touchscreen devices
Kumar, A., Paek, T., & Lee, B. (2012) · International Conference on Human Factors in Computing Systems · doi:10.1145/2207676.2208386 · Cited by 40 · see citing works
Hang on a sec!: effects of proactive mediation of phone conversations while driving
Iqbal, S. T., Horvitz, E., Ju, Y., & Mathews, E. (2011) · International Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979008 · Cited by 40 · cited 3× · see citing works
“…(Section 5.2) explores four distinct sub-topics; speech synthesis (e.g. Nass & Lee, 2000), content (e.g. Hoffmann et al., 2014), temporal aspects (e.g. Iqbal et al., 2011), and general speech production (Clark et al., 2016), with each study varying in the concepts explored within those sub-topics.”
BackgroundInfluentialThe role of spatial abilities and age in performance in an auditory computer navigation task
Pak, R., Czaja, S., Sharit, J., Rogers, W., & Fisk, A. (2008) · Computers in Human Behavior · doi:10.1016/j.chb.2008.05.010 · Cited by 40 · cited 1× · see citing works
“Finally, Pak et al. (2008) also examined auditory computer interfaces, though instead of assessing a prototype system as such, looked at the impact of age-related differences in spatial ability.”
BackgroundProceedings of the 2016 CHI Conference on Human Factors in Computing Systems
(2016) · International Conference on Human Factors in Computing Systems · doi:10.1145/2858036 · Cited by 39 · see citing works
Zhai, S.-M. (2014) · TCHI · doi:10.1145/2568193 · Cited by 36 · see citing works
A comparative study of speech and dialed input voice interfaces in rural India
Patel, N., Agarwal, S. K., Rajput, N., Nanavati, A., Dave, P., & Parikh, T. S. (2009) · International Conference on Human Factors in Computing Systems · doi:10.1145/1518701.1518709 · Cited by 36 · cited 2× · see citing works
“Task performance measures like the total number of turns (Le Bigot et al., 2007) percentage of tasks completed correctly (Oviatt et al., 2008) and task completion time (Patel et al., 2009) were also commonly used.”
BackgroundMethodThe impact of voice characteristics on user response in an interactive voice response system
Evans, R. E., & Kortum, P. (2010) · Interacting with computers · doi:10.1016/j.intcom.2010.07.001 · Cited by 34 · cited 3× · see citing works
“Perceived usability measures concentrated on quantifying concepts like perceived ease of use and learnability (e.g. Evans & Kortum, 2010), through Likert scale questionnaires.”
BackgroundMethodInfluentialEffect of modality on collaboration with a dialogue system
Bigot, L. L., Terrier, P., Amiel, V., Poulain, G., Jamet, E., & Rouet, J. (2007) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2007.07.002 · Cited by 34 · cited 2× · see citing works
“Task performance measures like the total number of turns (Le Bigot et al., 2007) percentage of tasks completed correctly (Oviatt et al., 2008) and task completion time (Patel et al., 2009) were also commonly used.”
BackgroundMethodA study of out-of-turn interaction in menu-based, IVR, voicemail systems
Perugini, S., Anderson, T. J., & Moroney, W. (2007) · International Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240770 · Cited by 33 · see citing works
Molnar, K., & Kletke, M. G. (1996) · Int. J. Hum. Comput. Stud. · doi:10.1006/ijhc.1996.0053 · Cited by 32 · see citing works
Hajukone: Developing an Open Source Olfactory Device
McGookin, D., & Escobar, D. (2016) · CHI Extended Abstracts · doi:10.1145/2851581.2892339 · Cited by 31
Effect of Machine Translation in Interlingual Conversation: Lessons from a Formative Study
Hara, K., & Iqbal, S. T. (2015) · International Conference on Human Factors in Computing Systems · doi:10.1145/2702123.2702407 · Cited by 31 · cited 1×
“Another paper explored the impact of spoken translation software on cross-lingual dialogues (Hara & Iqbal, 2015).”
BackgroundTeam reactions to voiced agent instructions in a pervasive game
Moran, S., Pantidi, N., Bachour, K., Fischer, J., Flintham, M., Rodden, T., Evans, S., & Johnson, S. (2013) · International Conference on Intelligent User Interfaces · doi:10.1145/2449396.2449445 · Cited by 30 · see citing works
A Multimodal In-Car Dialogue System That Tracks The Driver's Attention
Kousidis, S., Kennington, C., Baumann, T., Buschmeier, H., Kopp, S., & Schlangen, D. (2014) · International Conference on Multimodal Interaction · doi:10.1145/2663204.2663244 · Cited by 29 · cited 1× · see citing works
“Kousidis et al. (2014) also investigated dialogue systems in driving simulation tasks, when testing a situationally aware system that refrained from interruptions when higher driver attention was required.”
BackgroundEvaluating Perceptually Complementary Views for Network Exploration Tasks
Chang, C., Bach, B., Dwyer, T., & Marriott, K. (2017) · International Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3026024 · Cited by 28 · see citing works
To talk or not to talk with a computer
Batliner, A., Hacker, C., & Nöth, E. (2008) · Journal on Multimodal User Interfaces · doi:10.1007/s12193-009-0016-6 · Cited by 28 · cited 1×
“The technical challenges in terms of recognizing who is speaking (speaker diarization) and whether they are addressing the system are well researched (Batliner, Hacker, & Nöth, 2008).”
Background"You Talking to Me?" Exploring Voice in Self-Service User Interfaces
Johnson, G., & Coventry, L. (2001) · International journal of human computer interactions · doi:10.1207/s15327590ijhc1302_5 · Cited by 28 · see citing works
Beyond the Listening Test: An Interactive Approach to TTS Evaluation
Mendelson, J., & Aylett, M. (2017) · Interspeech · doi:10.21437/interspeech.2017-1438 · Cited by 27 · cited 1× · see citing works
“However, there are a number of studies published in other fields that are relevant to speech HCI work, including cognitive psychology, ergonomics, linguistics, and speech technology (e.g. Branigan et al., 2011; Large et al., 2017; Cowan & Branigan, 2015; Mendelson & Aylett, 2017).”
BackgroundSelf-citationImplicit user-adaptive system engagement in speech and pen interfaces
Oviatt, S., Swindells, C., & Arthur, A. M. (2008) · International Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357204 · Cited by 27 · cited 5× · see citing works
“Across the papers in our review, there was a range of objective and subjective concepts being measured, including task performance (e.g. Oviatt et al., 2008), production of lexis and syntax (e.g. Cowan et al., 2015), system usage (e.g. Schaffer et al., 2015), and user recall (e.g. Knutsen et al.,…”
BackgroundMethodInfluentialSears, A., Lin, M., & Karimullah, A. S. (2002) · Universal Access in the Information Society · doi:10.1007/s10209-002-0034-6 · Cited by 26
Designing Speech, Acoustic and Multimodal Interactions
Munteanu, C., Irani, P., Oviatt, S., Aylett, M., Penn, G., Pan, S.-M., Sharma, N., Rudzicz, F., Gomez, R., Cowan, B. R., et al. (2017) · CHI Extended Abstracts · doi:10.1145/3027063.3027086 · Cited by 24 · cited 4× · see citing works
“…and extended abstracts (e.g. Aylett et al., 2015; Cowan et al., 2016), debates or panel discussions (e.g. Cohen et al., 2016) workshop papers (e.g. Munteanu et al., 2017) and magazine articles, for instance those from Communications of the ACM (e.g. Shneiderman, 2000) or ACM Interactions (e.g.…”
BackgroundInfluentialSelf-citationSpeech-based interaction: myths, challenges, and opportunities
Munteanu, C., & Penn, G. (2014) · International Conference on Human-Computer Interaction with Mobile Devices and Services · doi:10.1145/2628363.2645671 · Cited by 24 · cited 1× · see citing works
“While interest in speech interfaces has been growing steadily (Cohen, Cheyer, Horvitz, El Kaliouby, & Whittaker, 2016; Munteanu et al., 2017; Munteanu & Penn, 2014) there is no clear idea of what forms the core of speech-based work in HCI.”
BackgroundSelf-citationOn user behaviour adaptation under interface change
Rosman, B., Ramamoorthy, S., Mahmud, M. M. H., & Kohli, P. (2014) · International Conference on Intelligent User Interfaces · doi:10.1145/2557500.2557535 · Cited by 24 · see citing works
Leahu, L., Cohn, M., & March, W. (2013) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/2470654.2466455 · Cited by 24 · cited 1× · see citing works
“Leahu et al. (2013) discuss the flexible, rather than static, nature of “human” and “machine” identity categories in this context, and possible experimental design implications.”
BackgroundTowards Understanding How Speech Output Affects Navigation System Credibility
Cowan, B. R., Gannon, D., Walsh, J., Kinneen, J., O'Keefe, E., & Xie, L.-X. (2016) · CHI Extended Abstracts · doi:10.1145/2851581.2892469 · Cited by 23 · cited 2× · see citing works
“We excluded works in progress and extended abstracts (e.g. Aylett et al., 2015; Cowan et al., 2016), debates or panel discussions (e.”
BackgroundTruschin, S., Schermann, M., Goswami, S., & Krcmar, H. (2014) · TCHI · doi:10.1145/2544066 · Cited by 23 · cited 5× · see citing works
“Effects of voice-matching were also investigated by Truschin et al. (2014). In research using speech to read emails during driving, an interface that used synthesized voices that matched email sender characteristics led to better comprehension scores than when a single voice was used for all emails. However, this nega…”
BackgroundInfluentialHuman perception of intended addressee during computer-assisted meetings
Lunsford, R., & Oviatt, S. (2006) · International Conference on Multimodal Interaction · doi:10.1145/1180995.1181002 · Cited by 23 · cited 1×
“Lunsford & Oviatt (2006) investigated the accuracy of people’s judgements of whether a speaker’s intended interlocutor is a human or computer.”
BackgroundA Multimodal Approach to Assessing User Experiences with Agent Helpers
Clark, L., Ofemile, A., Adolphs, S., & Rodden, T. (2016) · ACM Trans. Interact. Intell. Syst. · doi:10.1145/2983926 · Cited by 21 · cited 3× · see citing works
“, 2011), and general speech production (Clark et al., 2016), with each study varying in the concepts explored within those sub-topics.”
BackgroundInfluentialSelf-citationSimplified Audio Production in Asynchronous Voice-Based Discussions
Sivaraman, V., Yoon, D., & Mitros, P. (2016) · International Conference on Human Factors in Computing Systems · doi:10.1145/2858036.2858416 · Cited by 21 · see citing works
Modeling input modality choice in mobile graphical and speech interfaces
Schaffer, S., Schleicher, R., & Möller, S. (2015) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2014.11.004 · Cited by 21 · cited 2× · see citing works
“, 2017), user modelling (Schaffer et al., 2015), perceived sense of agency (Limerick et al.”
BackgroundMACCS: enabling communications for mobile workers within healthcare environments
Sammon, M., Brotman, L., Peebles, E., & Seligmann, D. (2006) · Mobile HCI · doi:10.1145/1152215.1152224 · Cited by 21 · cited 4×
“System measures like system logs appeared in fewer papers (N=18) and were useful for measuring what people used systems for (Sammon et al., 2006).”
BackgroundMethodInfluentialBigot, L. L., Jamet, E., Rouet, J., & Amiel, V. (2006) · Computers in Human Behavior · doi:10.1016/j.chb.2004.10.006 · Cited by 21 · cited 2× · see citing works
“Le Bigot et al. (2006) found performance with an information retrieval system improved over time, regardless of using speech or text.”
BackgroundMethodFischer, A., Price, K. J., & Sears, A. (2005) · International journal of human computer interactions · doi:10.1207/s15327590ijhc1903_1 · Cited by 21 · see citing works
Katz, J., Aspden, P., & Reich, W. A. (1997) · Behavior and Information Technology · doi:10.1080/014492997119860 · Cited by 21
Sasayaki: augmented voice web browsing experience
Sato, D., Zhu, S., Kobayashi, M., Takagi, H., & Asakawa, C. (2011) · Proceedings of the SIGCHI Conference on Human Factors in Computing Systems · doi:10.1145/1978942.1979353 · Cited by 20 · cited 2× · see citing works
“For example, asking users to evaluate voices (Dahlbäck, Wang, Nass, & Alwin, 2007) or assess an auditory web-browser (Sato, Zhu, Kobayashi, Takagi, & Asakawa, 2011).”
BackgroundWilkie, J. G. M., Jack, M. A., & Littlewood, P. (2004) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2004.08.001 · Cited by 20 · cited 5× · see citing works
“Another paper exploring studies on system politeness found that the use of different politeness strategies led people to have less positive attitudes towards an automated voice banking service (Wilkie et al., 2005).”
BackgroundMethodInfluentialVoiceLabel: using speech to label mobile sensor data
Harada, S., Lester, J., Patel, K., Saponas, T. S., Fogarty, J., Landay, J., & Wobbrock, J. (2008) · International Conference on Multimodal Interaction · doi:10.1145/1452392.1452407 · Cited by 20 · see citing works
Motion does matter: an examination of speech-based text entry on the move
Price, K. J., Lin, M., Feng, J.-J., Goldman, R., Sears, A., & Jacko, J. (2006) · Universal Access in the Information Society · doi:10.1007/s10209-005-0006-8 · Cited by 20 · see citing works
Howell, M., Love, S., & Turner, M. (2005) · Behavior and Information Technology · doi:10.1080/01449290512331319058 · Cited by 20 · see citing works
A comparison of mouse and speech input control of a text-annotation system
Bekker, M., van Nes, F. V., & Juola, J. (1990) · Behavior and Information Technology · doi:10.1080/01449299508914621 · Cited by 20 · cited 1×
“Bekker et al. (1995) examined the use of only speech and mouse input with a document-annotation system, observing more errors with speech and a user preference for mouse input.”
BackgroundBenjamin, A. (2017) · Compassion in Early Modern Literature and Culture · doi:10.1080/03643409.1978.12034012 · Cited by 20 · cited 1×
“Finally, one content-focused paper assessed evaluations of a spoken dialogue system designed to tailor its use of acknowledgements in accordance with the perceived ‘ephemeral emotions’ of its user (Tsukahara & Ward, 2001).”
BackgroundThe Effects on Decision Task Performance of Computer Synthetic Voice Output
DeHaemer, M., & Wallace, W. (1992) · Int. J. Man Mach. Stud. · doi:10.1016/0020-7373(92)90052-m · Cited by 20 · cited 1×
“Approaches commonly used in interaction design research such as cultural probes (DeHaemer & Wallace, 1992), contextual inquiry (Holtzblatt & Jones, 1993), and participatory design more generally (Schuler & Namioka, 1993) tended not to be used in the research we reviewed.”
MethodCarrot and stick 2.0: The benefits of natural and motivational prosody in computer-assisted learning
Wolff, S., & Brechmann, A. (2015) · Computers in Human Behavior · doi:10.1016/j.chb.2014.10.015 · Cited by 19 · see citing works
Comparison of speech-based in-car HMI concepts in a driving simulation study
Hofmann, H., Tobisch, V., Ehrlich, U., Berton, A., & Mahr, A. (2014) · International Conference on Intelligent User Interfaces · doi:10.1145/2557500.2557509 · Cited by 18 · cited 4×
“We were surprised to see that, although SASSI was deployed once in the reviewed papers (Hofmann et al., 2014), the scale has rarely been used in HCI publications.”
BackgroundMethodInfluentialMcCaughan, E., Prue, G., & Parahoo, K. (2009) · European Journal of Oncology Nursing · doi:10.1016/j.ejon.2009.04.001 · Cited by 18 · cited 2× · see citing works
“Following Mekler et al. (2014) we extracted the research aims, interaction type being researched, methodologies, and results from each paper.”
A longitudinal evaluation of hands-free speech-based navigation during dictation
Feng, J.-J., Sears, A., & Karat, C.-M. (2006) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2005.12.001 · Cited by 18 · see citing works
Kallinen, K., & Ravaja, N. (2005) · Behavior and Information Technology · doi:10.1080/01449290512331335609 · Cited by 18 · cited 3× · see citing works
“Kallinen & Ravaja (2005) compared perceptions and physiological reactions towards hearing news read on a computer at a slow or fast speech rate, observing the fast rate as more arousing yet less understandable than the slow rate.”
BackgroundMethodSocial Boundaries of Appropriate Speech in HCI: A Politeness Perspective
Clark, L. (2018) · Electronic workshops in computing · doi:10.14236/ewic/hci2018.76 · Cited by 17 · see citing works
Self-citationA pen and speech-based storytelling system for Chinese children
Wang, D., Li, J., Zhang, J., & Dai, G.-Z. (2008) · Computers in Human Behavior · doi:10.1016/j.chb.2008.03.014 · Cited by 17
Dialogue design in speech-mediated data-entry: the role of syntactic constraints and feedback
Murray, A. C., Jones, D., & Frankish, C. (1996) · Int. J. Hum. Comput. Stud. · doi:10.1006/ijhc.1996.0052 · Cited by 17 · see citing works
Computer aided conversation for severely physically impaired non-speaking people
Alm, N., Todman, J., Elder, L., & Newell, A. (1993) · INTERCHI · doi:10.1145/169059.169187 · Cited by 17 · cited 4× · see citing works
“Alm et al. (1993) assessed the usability of an assistive dialogue prototype for users who have severe physical disabilities and do not speak.”
BackgroundMethodInfluentialModelling human tutors' feedback to inform natural language interfaces for learning
Porayska-Pomsta, K., & Mellish, C. (2013) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2013.02.002 · Cited by 16 · cited 2× · see citing works
“The first of these papers evaluated a computer output model based on human tutor feedback (Porayska-Pomsta & Mellish, 2013), while the second examined the use of a hands-free audio device with a speech interface in a healthcare setting (Sammon, Brotman, Peebles, & Seligmann, 2006).”
BackgroundDoes voice anthropomorphism affect lexical alignment in speech-based human-computer dialogue?
Cowan, B. R., & Branigan, H. (2015) · Interspeech · doi:10.21437/interspeech.2015-75 · Cited by 16 · cited 1× · see citing works
“However, there are a number of studies published in other fields that are relevant to speech HCI work, including cognitive psychology, ergonomics, linguistics, and speech technology (e.g. Branigan et al., 2011; Large et al., 2017; Cowan & Branigan, 2015; Mendelson & Aylett, 2017).”
BackgroundFrom vocal to multimodal dialogue management
Melichar, M., & Cenek, P. (2006) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/1180995.1181008 · Cited by 15 · cited 2× · see citing works
“Examples include lexical choices (e.g. Porcheron et al., 2017) and modality use (e.g. (e.g. Melichar & Cenek, 2006).”
BackgroundHu, J., Winterboer, A., Nass, C., Moore, J., & Illowsky, R. (2007) · International Conference on Human Factors in Computing Systems · doi:10.1145/1240624.1240827 · Cited by 15 · cited 1× · see citing works
“Hu et al. (2007) compared “user-modeled summarize and refine (UMSR)” and “summarize and refine (SR)” approaches in voice-based browsing during simulated driving tasks.”
BackgroundInvestigating memory constraints on recall of options in interactive voice response system messages
Bigot, L. L., Caroux, L., Ros, C., Lacroix, A., & Botherel, V. (2013) · Behavior and Information Technology · doi:10.1080/0144929x.2011.563800 · Cited by 14 · cited 1× · see citing works
“User recall of menu options in IVR systems was significantly impaired when five or more options were presented, and with suffixes impairing memorization regardless of message (Le Bigot, Caroux, Ros, Lacroix, & Botherel, 2013).”
BackgroundAudio-visual cues distinguishing self- from system-directed speech in younger and older adults
Lunsford, R., Oviatt, S., & Coulston, R. (2005) · International Conference on Multimodal Interaction · doi:10.1145/1088463.1088494 · Cited by 14 · see citing works
Facilitating Development of Pragmatic Competence through a Voice-driven Video Learning Interface
Culbertson, G., Shen, S., Jung, M. F., & Andersen, E. (2017) · International Conference on Human Factors in Computing Systems · doi:10.1145/3025453.3025805 · Cited by 13 · see citing works
Speech-based cursor control using grids: modelling performance and comparisons with other solutions
Dai, L.-W., Goldman, R., Sears, A., & Lozier, J. (2005) · Behavior and Information Technology · doi:10.1080/01449290412331328563 · Cited by 13 · see citing works
Wang, Q., & Nass, C. (2005) · International Conference on Human Factors in Computing Systems · doi:10.1145/1054972.1055086 · Cited by 13 · cited 2× · see citing works
“Other measures included system recognition of user input (e.g. Oviatt et al., 2008), user agency (Limerick, Moore, & Coyle, 2015), and assessing user creativity and self-disclosure (Wang & Nass, 2005), and cognitive load (Truschin et al., 2014).”
BackgroundThe role of spoken feedback in experiencing multimodal interfaces as human-like
Qvarfordt, P., Jönsson, A., & Dahlbäck, N. (2003) · INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION · doi:10.1145/958432.958478 · Cited by 12 · see citing works
Visualisation improves the usability of voice-operated mobile phone services
Howell, M., Love, S., & Turner, M. (2006) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2006.03.002 · Cited by 12 · see citing works
Tutor design for speech-based interfaces
Hakulinen, J., Turunen, M., Salonen, E.-P., & Räihä, K.-J. (2004) · Symposium on Designing Interactive Systems · doi:10.1145/1013115.1013137 · Cited by 12 · cited 2×
“Hakulinen et al. (2004) explored the design and iterative development of an integrated tutor for teaching new users to operate a speech-based email reading application.”
BackgroundExplicit feedback from users attenuates memory biases in human-system dialogue
Knutsen, D., Bigot, L. L., & Ros, C. (2017) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2016.09.004 · Cited by 12 · cited 4× · see citing works
“Memory based research included measures of user recall in specific aspects of interaction (e.g. recall of system outputs (Knutsen et al., 2017)).”
BackgroundInfluentialNLify: lightweight spoken natural language interfaces via exhaustive paraphrasing
Han, S., Philipose, M., & Ju, Y. (2013) · Ubiquitous Computing · doi:10.1145/2493432.2493458 · Cited by 11
Adaptation and user expertise modelling in AthosMail
Jokinen, K. (2006) · Universal Access in the Information Society · doi:10.1007/s10209-005-0002-z · Cited by 11 · see citing works
Listening to your inner voices: investigating means for voice notifications
Bhatia, S., & McCrickard, S. (2006) · International Conference on Human Factors in Computing Systems · doi:10.1145/1124772.1124947 · Cited by 11 · cited 1×
“Another paper assessed the impact of voice familiarity on user reactions and levels of interruption and comprehension (Bhatia & McCrickard, 2006).”
BackgroundProceedings of the 18th ACM International Conference on Multimodal Interaction
(2016) · International Conference on Multimodal Interaction · doi:10.1145/2993148 · Cited by 11 · see citing works
Demonstration of sketch-thru-plan: a multimodal interface for command and control
Cohen, P. R., Buchanan, M., Kaiser, E. C., Corrigan, M., Lind, S., & Wesson, M. (2013) · International Conference on Multimodal Interaction · doi:10.1145/2522848.2531754 · Cited by 10 · cited 1×
“Speech can also be used solely as an input modality, often seen in ‘command and control’ of systems or devices (Cohen et al., 2013).”
BackgroundCould a dialog save your life?: analyzing the effects of speech interaction strategies while driving
Vetek, A., & Lemmelä, S. (2011) · International Conference on Multimodal Interaction · doi:10.1145/2070481.2070506 · Cited by 10 · see citing works
Interaction science SIG: overcoming challenges
Howes, A., Cowan, B. R., Janssen, C., Cox, A., Cairns, P., Hornof, A., Payne, S., & Pirolli, P. (2014) · CHI Extended Abstracts · doi:10.1145/2559206.2559208 · Cited by 8 · cited 1× · see citing works
“From this a more robust theory of language production and interlocutor perceptions may grow, which will be able to inform design and interaction science research (Howes et al., 2014) in the speech domain.”
BackgroundWilke, J., McInnes, F., Jack, M., & Littlewood, P. (2007) · Behavior and Information Technology · doi:10.1080/01449290600717783 · Cited by 8 · cited 2× · see citing works
“A number of papers took more of a usability engineering-based approach, comparing interface designs e.g. menu structures (e.g. Wilkie et al., 2005; Wilke et al., 2007), and observing their effect on user attitudes and performance.”
BackgroundLiapis, C. (2010) · Computers in Human Behavior · doi:10.1016/j.chb.2010.07.011 · Cited by 7 · see citing works
Derriks, B., & Willems, D. (1998) · Int. J. Hum. Comput. Stud. · doi:10.1006/ijhc.1997.0182 · Cited by 7 · cited 2× · see citing works
“These included corpus data (Derriks & Willems, 1998), focus groups (Cowan et al., 2017), user modelling (Schaffer et al., 2015), perceived sense of agency (Limerick et al., 2015) and physiological data (Kallinen & Ravaja, 2005).”
BackgroundMethodPaternò, F., Italy, M. '. 1. I. C. O. H.-C. I. W. M. D. A. S. 2. F., Association for Computing Machinery-Digital Library, ACM Special Interest Group on Computer-Human Interaction, & SIGs, A. (2016) · International Conference on Human-Computer Interaction with Mobile Devices and Services · doi:10.1145/2935334 · Cited by 7 · see citing works
Interactive Radio: A New Platform for Calm Computing
Aylett, M., Vazquez-Alvarez, Y., & Baillie, L. (2015) · CHI Extended Abstracts · doi:10.1145/2702613.2732785 · Cited by 5 · cited 1×
“We excluded works in progress and extended abstracts (e.g. Aylett et al., 2015; Cowan et al., 2016), debates or panel discussions (e.g. Cohen et al., 2016) workshop papers (e.g. Munteanu et al., 2017) and magazine articles, for instance those from Communications of the ACM (e.g. Shneiderman, 2000)…”
BackgroundSelf-citationMixed-initiative dialog management for speech-based interaction with graphical user interfaces
Löhr, A., & Brügge, B. (2008) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/1357054.1357205 · Cited by 4 · see citing works
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“Ramanarayanan et al. (2017) tested the efficacy of crowd source evaluations of engagement levels between non-native English speakers and a computer-assisted language learning (CALL) system.”
BackgroundSpeech-based navigation and error correction: a comprehensive comparison of two solutions
Feng, J.-J., Zhu, S., Hu, R., & Sears, A. (2011) · Universal Access in the Information Society · doi:10.1007/s10209-010-0185-9 · Cited by 4 · see citing works
Response Assertiveness in Human-Computer Dialogues
Buchheit, P., & Moher, T. G. (1990) · Int. J. Man Mach. Stud. · doi:10.1016/s0020-7373(05)80178-6 · Cited by 4 · see citing works
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Proceedings of ACL-2016 System Demonstrations
Pradhan, S., & Apidianaki, M. (2016) · Annual Meeting of the Association for Computational Linguistics · doi:10.18653/v1/p16-4 · Cited by 1
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Cited by
Sorted by citations
Rapp, A., Curti, L., & Boldi, A. (2021) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2021.102630 · Cited by 679 · see citing works
UX Research on Conversational Human-AI Interaction: A Literature Review of the ACM Digital Library
Zheng, Q., Tang, Y., Liu, Y., Liu, W., & Huang, Y. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3501855 · Cited by 114 · see citing works
“This was also found by prior literature reviews of CAs [41, 139].”
ResultHeuristic Evaluation of Conversational Agents
Langevin, R., Lordon, R. J., Avrahami, T., Cowan, B. R., Hirsch, T., & Hsieh, G. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445312 · Cited by 162 · see citing works
“Unlike other forms of human-computer interfaces, there is little consensus as to best practice for the design of conversational agents [2].”
BackgroundToward a design theory for virtual companionship
Strohmann, T., Siemon, D., Khosrawi-Rad, B., & Robra-Bissantz, S. (2022) · Human-Computer Interaction · doi:10.1080/07370024.2022.2084620 · Cited by 89 · see citing works
“This is consistent with further studies in which the participants question the relevance of a friendship-like relationship with machines, as well as a human-like CA design (Clark et al., 2019b; Doyle et al., 2019).”
BackgroundMethodResultInfluentialExamining Design Choices of Questionnaires in VR User Studies
Alexandrovsky, D., Putze, S., Bonfert, M., Höffner, S., Michelmann, P., Wenig, D., Malaka, R., & Smeddinck, J. D. (2020) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376260 · Cited by 85 · see citing works
“[9] note that evaluation of speech interfaces in real-world contexts is limited.”
BackgroundLLaMA-Omni2: LLM-based Real-time Spoken Chatbot with Autoregressive Streaming Speech Synthesis
Fang, Q., Zhou, Y., Guo, S., Zhang, S., & Feng, Y. (2025) · Annual Meeting of the Association for Computational Linguistics · doi:10.48550/arxiv.2505.02625 · Cited by 103
“Speech, as a critical interface for human-computer interaction, can significantly enhance both interaction efficiency and user experience (Clark et al., 2019).”
Cambre, J., & Kulkarni, C. (2019) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3359325 · Cited by 103 · see citing works
“Note that this paper introduces our framework, but the task of filling it in is far from complete: the most obvious omission is around how linguistic content affects speech-based interaction, which is thoroughly studied in [16].”
BackgroundMapping Perceptions of Humanness in Intelligent Personal Assistant Interaction
Doyle, P. R., Edwards, J., Dumbleton, O., Clark, L., & Cowan, B. R. (2019) · Proceedings of the 21st International Conference on Human-Computer Interaction with Mobile Devices and Services · doi:10.1145/3338286.3340116 · Cited by 100 · see citing works
“Validated metrics to quantify user perceptions are needed in the field [11].”
BackgroundSelf-citationEliciting and Analysing Users’ Envisioned Dialogues with Perfect Voice Assistants
Volkel, S. T., Buschek, D., Eiband, M., Cowan, B. R., & Hussmann, H. (2021) · International Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445536 · Cited by 95 · see citing works
“They are conversational agents available through a number of devices such as smartphones, computers, and smart speakers [16, 68], and are widely used in a number of contexts such as domestic [68] and automotive settings [9].”
BackgroundVoice as a Design Material: Sociophonetic Inspired Design Strategies in Human-Computer Interaction
Sutton, S. J., Foulkes, P., Kirk, D., & Lawson, S. (2019) · Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3290605.3300833 · Cited by 92 · see citing works
“But thus far, there has been little guidance of how to do this [12] and what the repercussions of VUI voices might be.”
BackgroundChoice of Voices: A Large-Scale Evaluation of Text-to-Speech Voice Quality for Long-Form Content
Cambre, J., Colnago, J., Maddock, J., Tsai, J. Y., & Kaye, J. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376789 · Cited by 90 · see citing works
Revolution or evolution? Speech interaction and HCI design guidelines
Murad, C., Munteanu, C., Cowan, B. R., & Clark, L. (2019) · IEEE Pervasive Computing · doi:10.1109/mprv.2019.2906991 · Cited by 84 · see citing works
Self-citationState-of-the-Art Human-Computer-Interaction in Metaverse
Lyu, Z. (2023) · International journal of human computer interactions · doi:10.1080/10447318.2023.2248833 · Cited by 82 · see citing works
“HCI is a rapidly growing field that presents both exciting new possibilities and formidable new obstacles (Clark et al., 2019; Ma et al., 2019; Vuletic et al., 2019).”
The Last Decade of HCI Research on Children and Voice-based Conversational Agents
Garg, R., Cui, H., Seligson, S., Zhang, B., Porcheron, M., Clark, L., Cowan, B. R., & Beneteau, E. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502016 · Cited by 75 · see citing works
“[27] conducted a systematic review of 99 articles across a range of HCI publication venues, focusing on non-embodied CAs.”
BackgroundMethodResultInfluentialSelf-citationWu, X.-Y. (2024) · System · doi:10.1016/j.system.2024.103498 · Cited by 114 · see citing works
Wu, Y., Rough, D., Bleakley, A., Edwards, J., Cooney, O., Doyle, P. R., Clark, L., & Cowan, B. R. (2020) · International Conference on Human-Computer Interaction with Mobile Devices and Services · doi:10.1145/3379503.3403563 · Cited by 77 · see citing works
“The proliferation of voice based Intelligent Personal Assistants (IPAs) like Google Assistant, on smart speakers and smartphones, has made speech a common interaction modality [8].”
BackgroundSelf-citationEnhancing Mobile Voice Assistants with WorldGaze
Mayer, S., Laput, G., & Harrison, C. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376479 · Cited by 74 · see citing works
“[14] offer a comprehensive survey on multimodal techniques incorporating speech input.”
BackgroundDoyle, P. R., Clark, L., & Cowan, B. R. (2021) · International Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445206 · Cited by 71 · see citing works
“ACM ISBN 978-1-4503-8096-6/21/05. https://doi.org/10.1145/3411764.3445206 CCS CONCEPTS • Human-centered computing → Natural language interfaces; HCI theory, concepts and models; Interaction design theory, concepts and paradigms; • Applied computing → Psychology.”
BackgroundInfluentialSelf-citationReitmaier, T., Wallington, E., Raju, D. K., Klejch, O., Pearson, J., Jones, M., Bell, P., & Robinson, S. (2022) · International Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517639 · Cited by 69 · see citing works
“This is an adapted, participatory twist to Wizard of Oz approaches commonly used to showcase and demonstrate novel voice user interfaces [12].”
MethodEvaluating Human-Language Model Interaction
Lee, M., Srivastava, M., Hardy, A., Thickstun, J., Durmus, E., Paranjape, A., Gerard-Ursin, I., Li, X. L., Ladhak, F., Rong, F., et al. (2022) · arXiv · doi:10.48550/arxiv.2212.09746 · Cited by 61 · see citing works
Kocaballi, A., Sezgin, E., Clark, L., Carroll, J. M., Huang, Y., Huh-Yoo, J., Kim, J., Kocielnik, R., Lee, Y.-C., Mamykina, L., et al. (2022) · Journal of Medical Internet Research · doi:10.2196/38525 · Cited by 61 · see citing works
“The fragmented nature of speech-based CA work, in particular, has recently been addressed [29,78].”
Self-citationAcceptability of Speech and Silent Speech Input Methods in Private and Public
Pandey, L., Hasan, K., & Arif, A. S. (2021) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445430 · Cited by 53 · see citing works
“With the recent advances in speech recognition technology [1, 44, 87, 91, 108], today’s voice-based commercial products [23, 48, 62, 116–118, 120] can perform streaming, highaccuracy, low-latency speech recognition [15, 68] to revolutionize human-computer interaction [29].”
BackgroundSiri, Echo and Performance: You have to Suffer Darling
Aylett, M., Cowan, B. R., & Clark, L. (2019) · CHI Extended Abstracts · doi:10.1145/3290607.3310422 · Cited by 57 · see citing works
“WoZ could be an especially good starting point[2].”
BackgroundSelf-citationDifferentially Private Speaker Anonymization
Shamsabadi, A., Srivastava, B. M., Bellet, A., Vauquier, N., Vincent, E., Maouche, M., Tommasi, M., & Papernot, N. (2022) · Proceedings on Privacy Enhancing Technologies · doi:10.48550/arxiv.2202.11823 · Cited by 56
“[4], [26] have enabled the deployment of voice-based services such as dictation, voice search and voice assistants in our daily life [15].”
BackgroundMeasuring Voice UX Quantitatively: A Rapid Review
Seaborn, K., & Urakami, J. (2021) · Extended Abstracts of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411763.3451712 · Cited by 55 · see citing works
“This recent and rapid progress has triggered a renewed interest in research on “the voice of the machine” [9,45].”
BackgroundCowan, B. R., Doyle, P. R., Edwards, J., Garaialde, D., Hayes-Brady, A., Branigan, H., Cabral, J. P., & Clark, L. (2019) · International Conference on Conversational User Interfaces · doi:10.1145/3342775.3342786 · Cited by 53 · see citing works
“Siri, Google Assistant, Amazon Echo) it is imperative that we develop an understanding of the mechanisms that drive language choices in HMD interactions [13].”
BackgroundSelf-citationReicherts, L., Rogers, Y., Capra, L., Wood, E., Duong, T. D., & Sebire, N. (2022) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3484221 · Cited by 52 · see citing works
“Clark et al. [15] have summarized empirical research comparing speech versus graphical interfaces on user performance and experience, which has shown mixed results.”
BackgroundRapp, A., Boldi, A., Curti, L., Perrucci, A., & Simeoni, R. (2023) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2023.2247596 · Cited by 55 · see citing works
“…from the majority of previous studies that investigated humanness in conversational agents relying on experiments or users ’ ex-post reports about their conversations with the agent (e.g., Clark et al., 2019; Doyle et al., 2019, 2021), we analyze real-world interactions between users and a chatbot.”
Exploring how politeness impacts the user experience of chatbots for mental health support
Bowman, R., Cooney, O., Newbold, J. W., Thieme, A., Clark, L., Doherty, G. J., & Cowan, B. R. (2023) · International Journal of Human-Computer Studies · doi:10.1016/j.ijhcs.2023.103181 · Cited by 57 · see citing works
Self-citationFoodScrap: Promoting Rich Data Capture and Reflective Food Journaling Through Speech Input
Luo, Y., Kim, Y.-H., Lee, B., Hassan, N., & Choe, E. K. (2021) · Conference on Designing Interactive Systems · doi:10.1145/3461778.3462074 · Cited by 50 · see citing works
“With the rise of speech recognition and natural language processing (NLP) technologies, speech has become a prevalent modality to interact with digital devices [19].”
BackgroundMarkus, A., Pfister, J., Carolus, A., Hotho, A., & Wienrich, C. (2024) · Computers and Education Open · doi:10.1016/j.caeo.2024.100176 · Cited by 49 · see citing works
MyMove: Facilitating Older Adults to Collect In-Situ Activity Labels on a Smartwatch with Speech
Kim, Y.-H., Chou, D., Lee, B., Danilovich, M., Lazar, A., Conroy, D. E., Kacorri, H., & Choe, E. K. (2022) · International Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517457 · Cited by 46 · see citing works
“speech, which is widely embedded in consumer devices and digital systems [22].”
BackgroundMildner, T., Cooney, O., Meck, A.-M., Bartl, M., Savino, G.-L., Doyle, P. R., Garaialde, D., Clark, L., Sloan, J., Wenig, N., et al. (2024) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642542 · Cited by 39 · see citing works
“Suggest-ing a lack of sufcient guidelines, practitioners adopt graphical user interfaces (GUIs) best practices to account for the unique af-fordances that CUIs present [16, 46, 56].”
BackgroundSelf-citationConversational Search - A Report from Dagstuhl Seminar 19461
Anand, A., Cavedon, L., Hagen, M., Joho, H., Sanderson, M., & Stein, B. (2020) · arXiv.org · doi:10.48550/arxiv.2005.08658 · Cited by 45
Determinants and consequences of trust in AI-based customer service chatbots
Prakash, A. V., Joshi, A., Nim, S., & Das, S. (2023) · Service Industries Journal · doi:10.1080/02642069.2023.2166493 · Cited by 55 · see citing works
A Review of Speech-centric Trustworthy Machine Learning: Privacy, Safety, and Fairness
Feng, T.-T., Hebbar, R., Mehlman, N., Shi, X., Kommineni, A., & Narayanan, S. S. (2022) · APSIPA Transactions on Signal and Information Processing · doi:10.1561/116.00000084 · Cited by 44 · see citing works
“In addition, speech-centric modeling has created numerous research topics in human behavior understanding, human-computer interface (HCI) [41], and social media analysis, involving several widely used speech modeling techniques like automatic speech recognition [110], speech emotion recognition [5], automatic speaker…”
BackgroundHuman, Hybrid, or Machine? Exploring the Trustworthiness of Voice-Based Assistants
Weidmüller, L. (2022) · Human-Machine Communication · doi:10.30658/hmc.4.5 · Cited by 43 · see citing works
“…items included were is reliable, gives security in information search, and respects people’s privacy, thereby incorporating common user (and designer) concerns regarding VBAs (Clark et al., 2019; Easwara Moorthy & Vu, 2015; Kinsella & Mutchler, 2020; Lei et al., 2018; Olson & Kemery, 2019).”
BackgroundMetaphors in Voice User Interfaces: A Slippery Fish
Desai, S., & Twidale, M. (2023) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3609326 · Cited by 42 · see citing works
Algorithm Awareness as an Important Internet Skill: The Case of Voice Assistants
Gruber, J., Hargittai, E., Karaoglu, G., & Brombach, L. (2021) · International journal of communication · doi:10.5167/uzh-204503 · Cited by 42 · see citing works
“Scholarly work about people’s experiences with voice assistants is often based on qualitative methods and comes from the field of human–computer interaction (see Clark et al., 2019, for a review).”
BackgroundConversational Agents for Health and Wellbeing
Kocaballi, A., Quiroz, J., Laranjo, L., Rezazadegan, D., Kocielnik, R., Clark, L., Liao, Q., Park, S., Moore, R. J., & Miner, A. S. (2020) · CHI Extended Abstracts · doi:10.1145/3334480.3375154 · Cited by 42 · see citing works
“This workshop aims to address current issues and potential benefits by bringing together conversational UX designers, medical informatics, HCI, machine learning, and design researchers investigating:”
BackgroundInfluentialSelf-citationAugmented Datasheets for Speech Datasets and Ethical Decision-Making
Papakyriakopoulos, O., Choi, A. S. G., Thong, W. E., Zhao, D., Andrews, J. T. A., Bourke, R., Xiang, A., & Koenecke, A. (2023) · ACM Conference on Fairness, Accountability, and Transparency (FAccT) · doi:10.1145/3593013.3594049 · Cited by 30 · see citing works
“Furthermore, it is valuable to perform in-the-wild experimentation including focus groups on developed SLT applications, which can uncover issues and harms affecting user populations [51].”
BackgroundFirefox Voice: An Open and Extensible Voice Assistant Built Upon the Web
Cambre, J., Williams, A. C., Razi, A., Bicking, I., Wallin, A., Tsai, J., Kulkarni, C., & Kaye, J. (2021) · Proceedings of the 2021 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3411764.3445409 · Cited by 39 · see citing works
“As voice interactions have become more commonplace, a growing body of work [19] has helped to illustrate when, where, why, how, and for whom voice can be most useful, and the key challenges and limitations of voice assistants.”
BackgroundDesai, S., & Chin, J. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581507 · Cited by 38 · see citing works
“As extensively noted in VUI literature, VUIs are not “conversational” in nature [24, 25, 31, 36, 45, 83].”
BackgroundAlghamdi, E., Halvey, M., & Nicol, E. (2024) · ACM Conversational User Interfaces 2024 · doi:10.1145/3640794.3665558 · Cited by 36 · see citing works
“For the current review, the list of terms was derived directly from similar papers that performed systematic reviews on speech-based and conversational interfaces [7, 16, 52].”
BackgroundMethodMultimodal Natural Human–Computer Interfaces for Computer-Aided Design: A Review Paper
Niu, H.-W., van Leeuwen, C. V., Hao, J., Wang, G.-X., & Lachmann, T. (2022) · Applied Sciences · doi:10.3390/app12136510 · Cited by 36 · see citing works
Rapp, A., Boldi, A., Curti, L., Perrucci, A., & Simeoni, R. (2023) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580995 · Cited by 24 · see citing works
“, [17, 25]), which may not refect what actually happened during the interaction, or on experiments, in which people are given instructions on how to converse with the agent and are not pursuing their own situated goals [3, 79, 95]: nonetheless, if interaction is not driven by a real goal that refects the fulflment of…”
BackgroundZhang, L., Jiang, L., Washington, N. L., Liu, A. A., Shao, J., Fourney, A., Morris, M., & Findlater, L. (2021) · Proc. ACM Hum. Comput. Interact. · doi:10.1145/3449235 · Cited by 34 · see citing works
“Researchers have recently called for more work in voice design theory, particularly in specific contexts [10], and the above discussion can inform the extension of existing theory to users as producers of a voice.”
BackgroundDesigning Voice Interfaces: Back to the (Curriculum) Basics
Murad, C., & Munteanu, C. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376522 · Cited by 34 · see citing works
Self-citationMental Workload and Language Production in Non-Native Speaker IPA Interaction
Wu, Y., Edwards, J., Cooney, O., Bleakley, A., Doyle, P. R., Clark, L., Rough, D., & Cowan, B. R. (2020) · CIU · doi:10.1145/3405755.3406118 · Cited by 33 · see citing works
“face interaction Current work on language productionin speech interface interactionalmostuniversally observes thelanguage choices ofL1 speakers. Even then, the volume of work on this topic is limited [9], with a focus on comparing language production in interactions between human-machine and human-human interlocutors.…”
BackgroundInfluentialSelf-citationParalinguistics-Aware Speech-Empowered Large Language Models for Natural Conversation
Kim, H., Seo, S., Jeong, K., Kwon, O., Kim, S., Kim, J., Lee, J., Song, E., Oh, M., Ha, J.-W., et al. (2024) · Neural Information Processing Systems · doi:10.52202/079017-4166 · Cited by 31 · see citing works
“Although automatic speech recognition (ASR) and text-to-speech (TTS) systems can be easily employed, the linguistic discrepancy between speech and text causes dialog inefficiencies and result in sub-optimal user experience [10, 11].”
Oh, J., Kim, W., Kim, S., Im, H., & Lee, S.-S. (2024) · International Conference on Human Factors in Computing Systems · doi:10.1145/3613904.3642193 · Cited by 30 · see citing works
“The WoZ method has been widely adopted in speech-based HCI studies [7, 12, 33].”
MethodWienrich, C., Carolus, A., Markus, A., Augustin, Y., Pfister, J., & Andreas Hotho, A. (2023) · Computers · doi:10.3390/computers12040077 · Cited by 31 · see citing works
“Intelligent voice assistants, or IVAs, which are integrated into smart speakers such as Amazon’s Alexa, are rapidly gaining popularity and becoming an integral part of everyday life [1,2].”
BackgroundShen, H., & Wang, M. (2023) · Computers in Human Behavior · doi:10.1016/j.chb.2023.107718 · Cited by 30 · see citing works
Do, T. D., McMahan, R. P., & Wisniewski, P. (2022) · International Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3517564 · Cited by 30 · see citing works
“Although early work found that there was no interaction between listener gender and speech fdelity [39], it is important to determine if older speech research applies to newer speech technologies [12, 56].”
BackgroundSpeech diversity and speech interfaces: considering an inclusive future through stammering
Clark, L., Cowan, B. R., Roper, A., Lindsay, S., & Sheers, O. (2020) · CIU · doi:10.1145/3405755.3406139 · Cited by 30 · see citing works
“3406139 [5], and attempts to move towards more conversational interactions with users [6], point to speech becoming more common in”
BackgroundSelf-citationCambre, J., Reig, S., Kravitz, Q., & Kulkarni, C. (2020) · Conference on Designing Interactive Systems · doi:10.1145/3357236.3395479 · Cited by 30 · see citing works
“Corresponding to a rise in voice assistant popularity, there has been a surge of interest within the HCI community in studying voice agents and other speech technology [15].”
BackgroundMaharjan, R., Rohani, D. A., Baekgaard, P., Bardram, J., & Doherty, K. (2021) · International Conference on Conversational User Interfaces · doi:10.1145/3469595.3469600 · Cited by 29 · see citing works
“And yet, there exists a general consensus among both HCI and healthcare researchers that limited design-oriented work has been conducted concerning CAs to date [12, 25, 28].”
BackgroundFinding a New Voice: Transitioning Designers from GUI to VUI Design
Murad, C., Munteanu, C., Cowan, B. R., & Clark, L. (2021) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3469595.3469617 · Cited by 30 · see citing works
“Research on designing usable VUIs is more limited than for other interaction types, as only recently have significant inroads been made in the VUI consumer space [9].”
BackgroundSelf-citationFrownOnError: Interrupting Responses from Smart Speakers by Facial Expressions
Yan, Y.-K., Yu, C., Zheng, W., Tang, R., Xu, X. "., & Shi, Y.-C. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376810 · Cited by 29 · see citing works
“For those who decides to interact with VUI, an important issue that affects user experience during the interaction is the conversation errors [7, 14], which require extra efforts for conversation recovery or lead to breakdowns [10].”
BackgroundCan Voice Assistants Sound Cute? Towards a Model of Kawaii Vocalics
Seaborn, K., Nam, S., Keckeis, J., & Itagaki, T. (2023) · CHI Extended Abstracts · doi:10.1145/3544549.3585656 · Cited by 28
“A variety of vocal qualities have been explored in computer voice over the past several decades [10, 43, 46].”
BackgroundHow context shapes the appropriateness of a robot’s voice
Torre, I., Latupeirissa, A., & McGinn, C. (2020) · IEEE International Symposium on Robot and Human Interactive Communication · doi:10.1109/ro-man47096.2020.9223449 · Cited by 28 · see citing works
A need for trust in conversational interface research
Edwards, J., & Sanoubari, E. (2019) · International Conference on Conversational User Interfaces · doi:10.1145/3342775.3342809 · Cited by 28 · see citing works
“Combining subjective, behavioral, and physiological measures of trust not only enrich the mixed methods approach proposed here for studying trust, but they may also, in combination, allow for creation of robust validated measures which are lacking in conversational HCI in general [2].”
BackgroundSelf-citationChin, J., Desai, S., Lin, S. (.-H., & Mejia, S. (2024) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3637365 · Cited by 27 · see citing works
“Conversely, the phenomenon of commercial VAs is nascent and lacks design guidelines and research on metaphors [16].”
BackgroundBräuer, P., & Mazarakis, A. (2022) · Computers in Human Behavior · doi:10.1016/j.chb.2022.107362 · Cited by 27 · see citing works
Commercial video games as a resource for mental health: A systematic literature review
Boldi, A., & Rapp, A. (2021) · Behaviour and Information Technology · doi:10.1080/0144929x.2021.1943524 · Cited by 44 · see citing works
Edwards, J., Liu, H., Zhou, T., Gould, S., Clark, L., Doyle, P. R., & Cowan, B. R. (2019) · International Conference on Conversational User Interfaces · doi:10.1145/3342775.3342785 · Cited by 27 · see citing works
“This would also answer calls in the field for more theory-based understanding of speech interface interactions more generally [13].”
BackgroundSelf-citationBräuer, P., & Mazarakis, A. (2022) · International journal of human computer interactions · doi:10.1080/10447318.2022.2160228 · Cited by 26 · see citing works
“As a result, the use of speech to interact with automated systems has grown in popularity (Clark et al., 2019; Lopatovska et al., 2020).”
BackgroundDoyle, P. R., Gessinger, I., Edwards, J., Clark, L., Dumbleton, O., Garaialde, D., Rough, D. J., Bleakley, A., Branigan, H. P., & Cowan, B. R. (2025) · ACM Transactions on Computer-Human Interaction · doi:10.1145/3729170 · Cited by 40 · see citing works
“However, although subjective measures are widely deployed, questions have been raised about the reliability and validity of the largely bespoke questionnaires normally used in these studies [19, 24, 52, 80].”
InfluentialSelf-citationWhat's The Talk on VUI Guidelines? A Meta-Analysis of Guidelines for Voice User Interface Design
Murad, C., Candello, H., & Munteanu, C. (2023) · Proceedings of the 5th International Conference on Conversational User Interfaces · doi:10.1145/3571884.3597129 · Cited by 24 · see citing works
“We derived the key-words directly from similar papers which performed meta-analyses on speech-based and conversational interfaces –the most relevant being a best paper from CHI 2019 which performed a large-scale survey on speech and voice interface papers in HCI [23] (see Table 1).”
MethodSelf-citationFaruk, L. I. D., Pal, D., Funilkul, S., Perumal, T., & Mongkolnam, P. (2024) · International journal of human computer interactions · doi:10.1080/10447318.2024.2359206 · Cited by 24 · see citing works
“Consequently, how to measure the UX of the CAs is an urgent yet unsolved question that has been pointed out by several recent research too (Clark et al., 2019; Dutsinma et al., 2022; Guerino & Valentim, 2020; Silva & Canedo, 2022; Tubin et al., 2022).”
Transcending the “Male Code”: Implicit Masculine Biases in NLP Contexts
Seaborn, K., Chandra, S., & Fabre, T. (2023) · International Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581017 · Cited by 24 · see citing works
“While speakingwith and listening to computers has a long history within the field of human-computer interaction (HCI), these recent industrial and commercial trends have reinvigorated interest in the voice of the machine [28, 95].”
BackgroundTicTacToes: Assessing Toe Movements as an Input Modality
Muller, F., Schmitt, D., Matviienko, A., Schön, D., Günther, S., Kosch, T., & Schmitz, M. (2023) · International Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3580954 · Cited by 24 · see citing works
“Besides voice-based interaction [12] which is known to be limited to quiet environments and poses privacy issues [46, 95], research proposed leveraging the movements of other body parts.”
The impact of the physical and social embodiment of voice user interfaces on user distraction
Moore, B. A., & Urakami, J. (2022) · Int. J. Hum. Comput. Stud. · doi:10.1016/j.ijhcs.2022.102784 · Cited by 24 · see citing works
Barger, A. S. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2024.1364054 · Cited by 23 · see citing works
“…interaction field with its varied ways to conduct research with new technologies – hosting co-design workshops, facilitating interviews or focus groups, gathering feedback through prototype testing, implementing WOz experiments, and assessing established commercial systems (Clark et al., 2019).”
Feijóo-García, P., Zalake, M. S., de Siqueira, A. G., Lok, B. C., & Hamza-Lup, F. G. (2021) · International Conference on Intelligent Virtual Agents · doi:10.1145/3472306.3478367 · Cited by 23 · see citing works
“Human-Computer Interaction (HCI) researchers have also explored the role that speech has on listeners’ perceptions of spoken interfaces’ credibility [11, 9, 8, 36], and some of them have done so concerning virtual humans [25, 33, 10].”
BackgroundCorrect Pronunciation Detection of the Arabic Alphabet Using Deep Learning
Ziafat, N., Ahmad, H. F., Fatima, I., Zia, M., Alhumam, A., & Rajpoot, K. (2021) · Applied Sciences · doi:10.3390/app11062508 · Cited by 23 · see citing works
“Automatic speech recognition (ASR) [4] has received considerable attention and recently made significant progress with its applications in mobile computing [5], human– computer interaction [6,7], information retrieval [8], and assisted communication [9].”
Background"Hi! I am the Crowd Tasker" Crowdsourcing through Digital Voice Assistants
Hettiachchi, D., Sarsenbayeva, Z., Allison, F., van Berkel, N., Dingler, T., Marini, G., Kostakos, V., & Gonçalves, J. (2020) · International Conference on Human Factors in Computing Systems · doi:10.1145/3313831.3376320 · Cited by 23 · see citing works
“However, research highlights that voice interfaces require better theories and more design guidelines, due to persistent usability issues [14, 48].”
BackgroundExploring Verbal Uncanny Valley Effects with Vague Language in Computer Speech
Clark, L., Ofemile, A., & Cowan, B. R. (2020) · Prosody, phonology and phonetics · doi:10.1007/978-981-15-6627-1_17 · Cited by 23 · see citing works
Self-citationCross-Corpora Spoken Language Identification with Domain Diversification and Generalization
Dey, S., Sahidullah, M., & Saha, G. (2023) · Computer Speech and Language · doi:10.1016/j.csl.2023.101489 · Cited by 22 · see citing works
“Across the globe, the number of users relying upon modern-day speech applications, such as automatic speech recognition (ASR), speaker recognition and verification , speech synthesis , speech emotion recognition (SER), will keep on increasing [14].”
BackgroundExploring Smart Speaker User Experience for People Who Stammer
Bleakley, A., Rough, D., Roper, A., Lindsay, S., Porcheron, M., Lee, M., Nicholson, S., Cowan, B. R., & Clark, L. (2022) · International ACM SIGACCESS Conference on Computers and Accessibility · doi:10.1145/3517428.3544823 · Cited by 22 · see citing works
“Prior research on speech as a modality in human-computer interaction (HCI) has demonstrated its benefts in improving access to interactive systems [12].”
BackgroundSelf-citationWhere is Vincent? Expanding our emotional selves with AI
Lee, M., Frank, L. E., de Kort, Y. A. W., & IJsselsteijn, W. A. (2022) · ACM Conference on Conversational User Interfaces (CUI) · doi:10.1145/3543829.3543835 · Cited by 24 · see citing works
“With rapid commercialization, we now see a growing use of CUIs like Alexa in everyday places; research interests accompany this growing use [22, 55].”
BackgroundCUI@CHI: Mapping Grand Challenges for the Conversational User Interface Community
Candello, H., Munteanu, C., Clark, L., Sin, J., Torres, M. I., Porcheron, M., Myers, C. M., Cowan, B. R., Fischer, J., Schlögl, S., et al. (2020) · CHI Extended Abstracts · doi:10.1145/3334480.3375152 · Cited by 22 · see citing works
“Second, this workshop is intended to further grow the Conversational User Interfaces (CUIs) community and scaffold this area at CHI.”
BackgroundInfluentialSelf-citation“I Didn’t Catch That, But I’ll Try My Best”: Anticipatory Error Handling in a Voice Controlled Game
Zargham, N., Pfau, J., Schnackenberg, T., & Malaka, R. (2022) · CHI Conference on Human Factors in Computing Systems · doi:10.1145/3491102.3502115 · Cited by 20 · see citing works
“Although the technical aspects of VUIs have been largely investigated, researchers agree on the stance that the user side of speech interaction is relatively less explored [8, 22, 47, 49].”
BackgroundIs Alexa like a computer? A search engine? A friend? A silly child? Yes.
Desai, S., & Twidale, M. (2022) · Proceedings of the 4th Conference on Conversational User Interfaces · doi:10.1145/3543829.3544535 · Cited by 20 · see citing works
“Others have even questioned whether some conversational user interfaces are (or indeed should be) in effect conversational [7, 10– 12, 15, 25, 26, 29].”
BackgroundKlein, A. M., Deutschländer, J., Kölln, K., Rauschenberger, M., & Escalona, M. J. (2023) · Journal of Software Evolution and Process · doi:10.1002/smr.2618 · Cited by 23 · see citing works
“31 Furthermore, there is a lack of appropriate attention to the context of use, as UX evaluation questionnaires usually focus on perceived product qualities or emotions.”
Building and Designing Expressive Speech Synthesis
Aylett, M., Clark, L., Cowan, B. R., & Torre, I. (2021) · The Handbook on Socially Interactive Agents · doi:10.1145/3477322.3477329 · Cited by 19 · see citing works
Self-citationVölkel, S., Meindl, S., & Hussmann, H. (2021) · International Conference on Conversational User Interfaces · doi:10.1145/3469595.3469605 · Cited by 19 · see citing works
“Voice assistants (VAs) have permeated our daily lives, being ubiquitous across a range of devices such as smartphones, smart speakers, and computers [10, 45], and in a variety of environments such as the”
BackgroundConversational User Interfaces on Mobile Devices: Survey
Jaber, R. N., & Mcmillan, D. (2020) · CIU · doi:10.1145/3405755.3406130 · Cited by 19 · see citing works
“Despite this, the majority of research on CUIs seems to focus elsewhere, with only 15% of papers referenced in the recent review by Clark et al. [19] focusing on mobile interaction even after excluding embodied interaction with devices such as stand-alone smart speakers and robots.”
BackgroundIntelligent Attributes of Voice Assistants and User’s Love for AI: A SEM-Based Study
Pal, D., Babakerkhell, M. D., Papasratorn, B., & Funilkul, S. (2023) · IEEE Access · doi:10.1109/access.2023.3286570 · Cited by 19 · see citing works
“Hence, from the user’s perspective since it helps in reducing their information redundancy or overload and create personalized offerings for them, thereby it makes the VAs suitable as life companions on which the users can trust and depend upon [52], [53], [54].”
BackgroundCognitive Load Estimation From Speech Commands to Simulated Aircraft
Vukovic, M., Stolar, M., & Lech, M. (2021) · IEEE/ACM Transactions on Audio Speech and Language Processing · doi:10.1109/taslp.2021.3057492 · Cited by 19 · see citing works
Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design
Zargham, N., Dubiel, M., Desai, S., Mildner, T., & Belz, H.-J. (2024) · International Conference on Mobile and Ubiquitous Multimedia (MUM) · doi:10.1145/3701571.3701608 · Cited by 15 · see citing works
Liesenfeld, A., Lopez, A., & Dingemanse, M. (2023) · SIGDIAL Conferences · doi:10.18653/v1/2023.sigdial-1.45 · Cited by 18 · see citing works
“As voice-based interactive technologies increasingly become part of everyday life, weaknesses in speech-to-text systems are rapidly becoming a key bottleneck (Clark et al., 2019).”
BackgroundConversational User Interfaces in Smart Homecare Interactions: A Conversation Analytic Case Study
Albert, S., Hamann, M., & Stokoe, E. (2023) · International Conference on Conversational User Interfaces · doi:10.1145/3571884.3597140 · Cited by 18 · see citing works
“For example, studies of the potential of CUIs for accessibility in a survey by Clark et al. 2019 tend to focus on the potential of speech technologies to enable people with a range of impairments to complete a specific set of performance-measurable tasks (see e.g., [5, 61, 71, 72]).”
BackgroundThe influence of conversational role on phonetic alignment toward voice-AI and human interlocutors
Zellou, G., Cohn, M., & Kline, T. (2021) · Language, Cognition and Neuroscience · doi:10.1080/23273798.2021.1931372 · Cited by 18 · see citing works
Systematic Review of Design Guidelines for Full-Body Interactive Games
Subramanian, S., Skjaeret-Maroni, N., & Dahl, Y. (2020) · Interacting with computers · doi:10.1093/iwc/iwaa026 · Cited by 18 · see citing works
Ringfort-Felner, R., Laschke, M., Neuhaus, R., Theofanou-Fülbier, D., & Hassenzahl, M. (2022) · Nordic Conference on Human-Computer Interaction · doi:10.1145/3546155.3546699 · Cited by 15 · see citing works
“In fact, recent reviews on voice assistants indicate a lack of concrete design guidance for the next generation of IPAs [12].”
BackgroundMethodInfluentialHow Do Illiterate People Interact with an Intelligent Voice Assistant?
da Silva, T. H. O., Furtado, V., Furtado, E. S., Mendes, M. S., Almeida, V. A. F., & Sales, L. (2022) · International Journal of Human-Computer Interaction · doi:10.1080/10447318.2022.2121219 · Cited by 18 · see citing works
“…works previously described analyzed the accuracy of recognition of spoken vocabulary and the performance of users when performing tasks with an IVA, also known as task performance (Clark et al., 2019), in order to assess how prepared the system is to understand the diversity of users ’ discourses.”
BackgroundEthics of Conversational User Interfaces
Lee, M., Sin, J., Laban, G., Kraus, M., Clark, L., Porcheron, M., Cowan, B. R., Følstad, A., Munteanu, C., & Candello, H. (2022) · CHI Extended Abstracts · doi:10.1145/3491101.3503699 · Cited by 17 · see citing works
“Previous CUI research spans how to best design CUI interactions [4, 5, 9, 16, 17, 34, 44], such as tools and heuristics on voice-based interfaces [8, 36] and sociolinguistic considerations [9, 11, 27], as well as diverse ways to understand people’s difer-ent preferences or perceptions regarding…”
BackgroundSelf-citationHow do voice acoustics affect the perceived trustworthiness of a speaker? A systematic review
Maltezou-Papastylianou, C., Scherer, R., & Paulmann, S. (2025) · Frontiers in Psychology · doi:10.3389/fpsyg.2025.1495456 · Cited by 16 · see citing works
“…settings tends to refer to either canned speech (i.e., unchangeable pre-recorded speech samples) or synthesised speech, both seen in voice research (Nass and Brave, 2005; Kaur and Singh, 2023; Clark et al., 2019; Cambre and Kulkarni, 2019; Weinschenk and Barker, 2000; Kang and Heide, 1992).”
Qualitative Approaches to Voice UX
Seaborn, K., Urakami, J., Pennefather, P., & Miyake, N. (2024) · ACM Computing Surveys · doi:10.1145/3658666 · Cited by 18 · see citing works
“Qualitative research, however, is rarely characterized as posi-tivist.”
Influential
- Authors
- Clark, L., Doyle, P., Garaialde, D., Gilmartin, E., Schlögl, S., Edlund, J., Aylett, M., Cabral, J., Munteanu, C., Edwards, J., & R Cowan, B.
- Affiliations
- University College Dublin (IE)
- Trinity College Dublin (IE)
- Universität Innsbruck (AT)
- KTH Royal Institute of Technology (SE)
- CereProc (United Kingdom) (GB)
- University of Toronto (CA)
- School of Information and Communication Studies, University College Dublin, Belfield, Dublin 4, Ireland
- Corresponding author
- Clark, Leigh
- ORCID
- Venue
- Interacting with Computers
- Publisher
- Oxford University Press (OUP)
- Published
- 2019-06-01
- Volume
- 31
- Issue
- 4
- Pages
- 349-371
- ISSN
- 0953-5438 (ISSN-L)
- 1873-7951
- OpenAlex
- W2896893982
- Cited by
- 193
- References
- 175
- Citations by year
- 2026: 12 · 2025: 27 · 2024: 28 · 2023: 34 · 2022: 37 · 2021: 27 · 2020: 19 · 2019: 9
- FWCI
- 10.61
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Licence
- academic.oup.com/journals/pages/open_access/funder_policies/chorus/standard_publication_model (vor)
- Locations
- Interacting with Computers (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- arXiv (Cornell University)
- Funders
- Irish Research Council
- Topics
- Physical Sciences › Computer Science › Artificial Intelligence › Speech and dialogue systems
- Physical Sciences › Computer Science › Human-Computer Interaction › Usability and User Interface Design
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- speech interfaces, usability evaluation, Wizard of Oz, interactive voice response, assistive technology, accessibility, virtual assistants, user memory, speech production, modality comparison, research gaps, measurement reliability
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